MemoryDecoder Gpt2 Small

Name: MemoryDecoder Gpt2 Small
Author: Clover-Hill

1 language

license:apache-2.0

Clover-Hill

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OTHER

2508.09874B params

New

89 downloads

Early-stage

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Edge AI:

Mobile

Laptop

Server

5607GB+ RAM

Mobile

Laptop

Server

Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

2336GB+ RAM

Code Examples

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

Quick Startpythontransformers

from memDec import MemoryDecoder
import transformers
from transformers import AutoModelForCausalLM
from loguru import logger

# Define paths to your models
base_lm_path = "gpt2-xl"  # or any GPT2 variant
knn_generator_path = "Clover-Hill/MemoryDecoder-gpt2-small"

# Load tokenizer and models
tokenizer = transformers.AutoTokenizer.from_pretrained(base_lm_path)
base_lm = AutoModelForCausalLM.from_pretrained(base_lm_path)
knn_generator = AutoModelForCausalLM.from_pretrained(knn_generator_path)

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