Instructions to use bigscience/bloom-7b1-petals with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigscience/bloom-7b1-petals with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bigscience/bloom-7b1-petals")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bigscience/bloom-7b1-petals") model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-7b1-petals", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bigscience/bloom-7b1-petals with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bigscience/bloom-7b1-petals" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bigscience/bloom-7b1-petals", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bigscience/bloom-7b1-petals
- SGLang
How to use bigscience/bloom-7b1-petals 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/bloom-7b1-petals" \ --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/bloom-7b1-petals", "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/bloom-7b1-petals" \ --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/bloom-7b1-petals", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bigscience/bloom-7b1-petals with Docker Model Runner:
docker model run hf.co/bigscience/bloom-7b1-petals
Commit History
-
Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (7f6c8ff3e95ab249ad2046799dea440adda5e387) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>0b230a6 -
Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (81046e41f2dbc21f32ab727548000a6415e9724b) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>7dc4b45
-
Fix architecture (#1)
- Fix architecture (ba2fa8f8bc1f86b233d541fafd87114161b7661e) Co-authored-by: Lewis Tunstall <lewtun@users.noreply.huggingface.co>782803a
-
Create README.md
eaba8f8 -
Update config.json
bd1b5f2 -
push-o-matic
5de3946 -
initial commit
9ad060e