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