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
- 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
Add metadata and link to paper
#12 opened about 1 year ago
by
nielsr
can you provide wikitest ppl and c4 ppl separately?
#11 opened about 2 years ago
by
sheropen-2
Can you provide more details on the training?
1
#10 opened about 2 years ago
by
dequ777
Any plans to use MQA (multi-query attention) or GQA (grouped-query attention) in the future?
#9 opened about 2 years ago
by
graefics
Efficient Inference Kernel Support for 1.58bit.
❤️ 10
#8 opened about 2 years ago
by
LeiWang1999
This code from BitLinear doesn't make sense
1
#7 opened about 2 years ago
by
qmsoqm
Is it bitnet {-1,0,1}?
4
#6 opened about 2 years ago
by
Remek
ValueError: Tokenizer class BitnetTokenizer does not exist or is not currently imported.
👍 2
4
#5 opened about 2 years ago
by
ryanzhangofficial
Longer inference time
2
#4 opened about 2 years ago
by
dittops
Why are these models fp32?
👀 3
5
#2 opened about 2 years ago
by
supercharge19
Is there a chat/instruct model in plans?
2
#1 opened about 2 years ago
by
MrVodnik