Instructions to use bigscience/bloom-7b1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigscience/bloom-7b1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bigscience/bloom-7b1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bigscience/bloom-7b1") model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-7b1") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bigscience/bloom-7b1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bigscience/bloom-7b1" # 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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bigscience/bloom-7b1
- SGLang
How to use bigscience/bloom-7b1 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" \ --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", "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" \ --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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bigscience/bloom-7b1 with Docker Model Runner:
docker model run hf.co/bigscience/bloom-7b1
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README.md
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pipeline_tag: text-generation
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# <span style="color:red"><b>WARNING:</b> This is an <b>intermediary checkpoint</b>. It is not fully trained yet. You might want to use [Bloom-1B3](https://huggingface.co/bigscience/bloom-1b3) if you want a model that has completed training.</span>
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<h1 style='text-align: center '>BLOOM LM</h1>
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<h2 style='text-align: center '><em>BigScience Large Open-science Open-access Multilingual Language Model</em> </h2>
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<h3 style='text-align: center '>Model Card</h3>
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And multiple different metrics for specific tasks. _(More evaluation metrics forthcoming upon completion of evaluation protocol.)_
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### Factors
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*This section lists some different aspects of
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- Language, such as English or Yoruba
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As of 25.May.2022, 15:00 PST:
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- Training Loss: 2.
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- Validation Loss: 2.2
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</details>
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<p> </p>
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pipeline_tag: text-generation
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---
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<h1 style='text-align: center '>BLOOM LM</h1>
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<h2 style='text-align: center '><em>BigScience Large Open-science Open-access Multilingual Language Model</em> </h2>
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<h3 style='text-align: center '>Model Card</h3>
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And multiple different metrics for specific tasks. _(More evaluation metrics forthcoming upon completion of evaluation protocol.)_
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### Factors
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*This section lists some different aspects of BLOOM models. Its focus is on those aspects that are likely to give rise to high variance in model behavior.*
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- Language, such as English or Yoruba
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As of 25.May.2022, 15:00 PST:
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- Training Loss: 2.3
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- Validation Loss: 2.9
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- Perplexity: 16
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</details>
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<p> </p>
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