Instructions to use 1bitLLM/bitnet_b1_58-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1bitLLM/bitnet_b1_58-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="1bitLLM/bitnet_b1_58-3B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("1bitLLM/bitnet_b1_58-3B") model = AutoModelForCausalLM.from_pretrained("1bitLLM/bitnet_b1_58-3B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 1bitLLM/bitnet_b1_58-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "1bitLLM/bitnet_b1_58-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "1bitLLM/bitnet_b1_58-3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/1bitLLM/bitnet_b1_58-3B
- SGLang
How to use 1bitLLM/bitnet_b1_58-3B 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 "1bitLLM/bitnet_b1_58-3B" \ --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": "1bitLLM/bitnet_b1_58-3B", "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 "1bitLLM/bitnet_b1_58-3B" \ --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": "1bitLLM/bitnet_b1_58-3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 1bitLLM/bitnet_b1_58-3B with Docker Model Runner:
docker model run hf.co/1bitLLM/bitnet_b1_58-3B
ValueError: Tokenizer class BitnetTokenizer does not exist or is not currently imported.
Updated transformers library with pip install --upgrade transformers, but still receive following error:
ValueError Traceback (most recent call last)
in <cell line: 3>()
1 from transformers import AutoTokenizer, AutoModelForCausalLM
2
----> 3 tokenizer = AutoTokenizer.from_pretrained("1bitLLM/bitnet_b1_58-3B", trust_remote_code=True)
4 model = AutoModelForCausalLM.from_pretrained("1bitLLM/bitnet_b1_58-3B")
/usr/local/lib/python3.10/dist-packages/transformers/models/auto/tokenization_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs)
839 tokenizer_class = tokenizer_class_from_name(tokenizer_class_candidate)
840 if tokenizer_class is None:
--> 841 raise ValueError(
842 f"Tokenizer class {tokenizer_class_candidate} does not exist or is not currently imported."
843 )
ValueError: Tokenizer class BitnetTokenizer does not exist or is not currently imported.
Couple months later and I'm still getting this as well. Unfortunate.
The same with me :(
i am also getting this
Any updates on this?