Instructions to use NousResearch/OLMo-Bitnet-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NousResearch/OLMo-Bitnet-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NousResearch/OLMo-Bitnet-1B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NousResearch/OLMo-Bitnet-1B", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("NousResearch/OLMo-Bitnet-1B", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use NousResearch/OLMo-Bitnet-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NousResearch/OLMo-Bitnet-1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NousResearch/OLMo-Bitnet-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/NousResearch/OLMo-Bitnet-1B
- SGLang
How to use NousResearch/OLMo-Bitnet-1B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "NousResearch/OLMo-Bitnet-1B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NousResearch/OLMo-Bitnet-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "NousResearch/OLMo-Bitnet-1B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NousResearch/OLMo-Bitnet-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use NousResearch/OLMo-Bitnet-1B with Docker Model Runner:
docker model run hf.co/NousResearch/OLMo-Bitnet-1B
How to run the model? `KeyError: 'cache_position'`
To load the model in google colab
!pip install omegaconf
!pip install botocore boto3 cached_path
!pip install accelerate
Then load model as given in Model CArd:
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, TextStreamer
tokenizer = AutoTokenizer.from_pretrained("NousResearch/OLMo-Bitnet-1B")
model = AutoModelForCausalLM.from_pretrained("NousResearch/OLMo-Bitnet-1B",
torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
streamer = TextStreamer(tokenizer)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer,
pad_token_id=tokenizer.eos_token_id,
temperature=0.8, repetition_penalty=1.1, do_sample=True,streamer=streamer)
pipe("The capitol of Paris is", max_new_tokens=256)
This gives error: KeyError: 'cache_position'
What is happening. How is it passing cache_position?
I upgraded transformers model but I kept getting other error like:
ValueError: 'olmo' is already used by a Transformers config, pick another name.
Same here
Were you able to solve this issue?
"ValueError: 'olmo' is already used by a Transformers config, pick another name."
While instantiating the model, just remove the trust_remote_code
model = AutoModelForCausalLM.from_pretrained("NousResearch/OLMo-Bitnet-1B",
torch_dtype=torch.bfloat16)
While instantiating the model, just remove the trust_remote_code
model = AutoModelForCausalLM.from_pretrained("NousResearch/OLMo-Bitnet-1B",
torch_dtype=torch.bfloat16)
This doesn't fix "ValueError: 'olmo' is already used by a Transformers config, pick another name.". Moreover, the error appears in the first line (when importing hf_olmo). It didn't even reach the line where trust_remote_code is set :-(
Same here