Dayhoff-3b-GR-HM-c

220
1
3.0B
—
by
microsoft
Other
OTHER
3B params
New
220 downloads
Early-stage
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
7GB+ RAM
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
3GB+ RAM

Code Examples

How to Get Started with the Modelpythontransformers
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed

set_seed(0)
torch.set_default_device("cuda")

model = AutoModelForCausalLM.from_pretrained('microsoft/Dayhoff-3b-GR-HM-c')
tokenizer = AutoTokenizer.from_pretrained('microsoft/Dayhoff-3b-GR-HM-c', trust_remote_code=True)


inputs = tokenizer(tokenizer.bos_token, return_tensors="pt", return_token_type_ids=False)

outputs = model.generate(inputs['input_ids'],max_length=50,do_sample=True)
sequence = tokenizer.batch_decode(outputs,skip_special_tokens=True)
print(sequence)
How to Get Started with the Modelpythontransformers
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed

set_seed(0)
torch.set_default_device("cuda")

model = AutoModelForCausalLM.from_pretrained('microsoft/Dayhoff-3b-GR-HM-c')
tokenizer = AutoTokenizer.from_pretrained('microsoft/Dayhoff-3b-GR-HM-c', trust_remote_code=True)


inputs = tokenizer(tokenizer.bos_token, return_tensors="pt", return_token_type_ids=False)

outputs = model.generate(inputs['input_ids'],max_length=50,do_sample=True)
sequence = tokenizer.batch_decode(outputs,skip_special_tokens=True)
print(sequence)

Deploy This Model

Production-ready deployment in minutes

Together.ai

Instant API access to this model

Fastest API

Production-ready inference API. Start free, scale to millions.

Try Free API

Replicate

One-click model deployment

Easiest Setup

Run models in the cloud with simple API. No DevOps required.

Deploy Now

Disclosure: We may earn a commission from these partners. This helps keep LLMYourWay free.