Instructions to use bigscience/bloomz-7b1-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigscience/bloomz-7b1-mt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bigscience/bloomz-7b1-mt")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bigscience/bloomz-7b1-mt") model = AutoModelForCausalLM.from_pretrained("bigscience/bloomz-7b1-mt") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use bigscience/bloomz-7b1-mt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bigscience/bloomz-7b1-mt" # 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-7b1-mt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bigscience/bloomz-7b1-mt
- SGLang
How to use bigscience/bloomz-7b1-mt 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-7b1-mt" \ --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-7b1-mt", "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-7b1-mt" \ --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-7b1-mt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bigscience/bloomz-7b1-mt with Docker Model Runner:
docker model run hf.co/bigscience/bloomz-7b1-mt
Error download
git clone https://huggingface.co/bigscience/bloomz-7b1-mt
Cloning into 'bloomz-7b1-mt'...
remote: Enumerating objects: 746, done.
remote: Counting objects: 100% (3/3), done.
remote: Compressing objects: 100% (3/3), done.
remote: Total 746 (delta 0), reused 3 (delta 0), pack-reused 743
Receiving objects: 100% (746/746), 73.84 KiB | 18.46 MiB/s, done.
Resolving deltas: 100% (321/321), done.
Filtering content: 100% (6/6), 1.20 GiB | 3.15 MiB/s, done.
Encountered %!d(MISSING) file(s) that may not have been copied correctly on Windows:
pytorch_model.bin
See: git lfs help smudge for more details.
Encountered %!d(MISSING) file(s) that may not have been copied correctly on Windows: is expected; Everything should work fine if you're not on Windows