Instructions to use bigscience/bloomz-p3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigscience/bloomz-p3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bigscience/bloomz-p3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bigscience/bloomz-p3") model = AutoModelForCausalLM.from_pretrained("bigscience/bloomz-p3") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bigscience/bloomz-p3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bigscience/bloomz-p3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bigscience/bloomz-p3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bigscience/bloomz-p3
- SGLang
How to use bigscience/bloomz-p3 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 "bigscience/bloomz-p3" \ --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": "bigscience/bloomz-p3", "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 "bigscience/bloomz-p3" \ --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": "bigscience/bloomz-p3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bigscience/bloomz-p3 with Docker Model Runner:
docker model run hf.co/bigscience/bloomz-p3
Why does this take so long to load?
Every time I try to run it, it spends so long just to load the model. So long that it times out.
Every time I try to run it, it spends so long just to load the model. So long that it times out.
If you're referring to the Hosted Inference API, that's because there is no GPU provisioned for this model and the model is huge, so it will take very very long.
If you want to run it, you need to download the model and run it on your own hardware, sorry :(
Here are some guidelines for running it: https://huggingface.co/bigscience/bloomz/discussions/18#636b6ad958a8f9348d0ab82c
We should probably disable the widget as it may be confusing then
Ah, got it.
Thanks. I was just attempting to try it out. If it does what I think it does, then it could be just as good if not better than GPT-3.
Nice work, I love open source.
Even if I can’t run it :(
FYI removed the widget to prevent more confusion about this: https://huggingface.co/bigscience/bloomz-p3/commit/51f3d0d7079a37501554eb7ce2558012bb96d062