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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
File size: 838 Bytes
2010c83 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | __all__ = [
"OLMoError",
"OLMoConfigurationError",
"OLMoCliError",
"OLMoEnvironmentError",
"OLMoNetworkError",
"OLMoCheckpointError",
]
class OLMoError(Exception):
"""
Base class for all custom OLMo exceptions.
"""
class OLMoConfigurationError(OLMoError):
"""
An error with a configuration file.
"""
class OLMoCliError(OLMoError):
"""
An error from incorrect CLI usage.
"""
class OLMoEnvironmentError(OLMoError):
"""
An error from incorrect environment variables.
"""
class OLMoNetworkError(OLMoError):
"""
An error with a network request.
"""
class OLMoCheckpointError(OLMoError):
"""
An error occurred reading or writing from a checkpoint.
"""
class OLMoThreadError(Exception):
"""
Raised when a thread fails.
"""
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