deep-ignorance-unfiltered
7.5K
2
6.9B
1 language
license:apache-2.0
by
EleutherAI
Language Model
OTHER
6.9B params
New
8K downloads
Early-stage
Edge AI:
Mobile
Laptop
Server
16GB+ RAM
Mobile
Laptop
Server
Quick Summary
AI model with specialized capabilities.
Device Compatibility
Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
7GB+ RAM
Code Examples
pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])pythontransformers
from transformers import GPTNeoXForCausalLM, AutoTokenizer
model = GPTNeoXForCausalLM.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/deep-ignorance-strong-filter-pt-weak-filter-anneal",
revision="global_step11921",
)
inputs = tokenizer("Hello, I am", return_tensors="pt")
tokens = model.generate(**inputs)
tokenizer.decode(tokens[0])Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
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author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
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@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
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}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
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}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
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}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
}Citationtext
@article{obrien2025deepignorance,
title={Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs},
author={O'Brien, Kyle and Casper, Stephen and Anthony, Quentin and Korbak, Tomek and Kirk, Robert and Davies, Xander and Mishra, Ishan and Irving, Geoffrey and Gal, Yarin and Biderman, Stella},
journal={arXiv preprint arXiv:2508.06601},
year={2025}
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