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# BLOOM, a version for Petals |
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This model is a version of [bigscience/bloom-7b1](https://huggingface.co/bigscience/bloom-7b1) |
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post-processed to be run at home using the [Petals](https://github.com/bigscience-workshop/petals#readme) swarm. |
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**Note:** Petals is developed to run 100B+ models |
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like the [full-scale BLOOM](https://huggingface.co/bigscience/bloom-petals) or [BLOOMZ](https://huggingface.co/bigscience/bloomz-petals). |
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This model is provided for testing purposes only. It may be more efficient to run the original version of it locally. |
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Please check out: |
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- The [original model card](https://huggingface.co/bigscience/bloom-7b1) |
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to learn about the model's capabilities, specifications, and terms of use. |
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- The [Petals repository](https://github.com/bigscience-workshop/petals#readme) |
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to learn how to install Petals and run this model over the Petals swarm. |
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We provide minimal code examples below. |
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## Using the model |
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```python |
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from petals import DistributedBloomForCausalLM |
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model = DistributedBloomForCausalLM.from_pretrained("bigscience/bloom-7b1-petals") |
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# Embeddings & prompts are on your device, BLOOM blocks are distributed across the Internet |
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inputs = tokenizer("A cat sat", return_tensors="pt")["input_ids"] |
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outputs = model.generate(inputs, max_new_tokens=5) |
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print(tokenizer.decode(outputs[0])) # A cat sat on a mat... |
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``` |
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## Serving the model blocks |
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```bash |
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python -m petals.cli.run_server bigscience/bloom-7b1-petals |
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``` |