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dalaipy (NOTICE: THIS IS DEPRECATED, USE THE OFFICIAL BINDINGS FOR LLAMA.CPP, WILL RUN FASTER AND LESS BUGGY )

A Python Wrapper for Dalai

Dalai is a simple, and easy way to run LLaMa and Alpaca locally.

Installation

pip install dalaipy==2.0.2

https://pypi.org/project/dalaipy/2.0.2/

Instructions

  1. Go to Dalai, and set up your model of choice on your system (either Mac, Windows, or Linux). The readme provides clear explanations!
  2. Once you can run npx dalai serve, run the server and test out your model of choice.
  3. Install dalaipy per the instructions above, and make your first request:
from dalaipy.src import Dalai

model = Dalai()
# your_model can be one of the following, "alpaca.7B", "alpaca.13B", "llama.7B", "llama.13B", "llama.30B", or "llama.65B", and is dictated by which model you installed
request_dict = model.generate_request("What is the capital of the United States?", your_model)
print(model.request(request_dict))

Credits

@cocktailpeanut - the owner of Dalai

@quadrismegistus - made a notebook with the original idea of using python-socketio to communicate with the web server

Docs

Dalai Class

  • generate_request() - model.generate_request(prompt, model)

    • prompt: (required) the prompt string
    • model: (required) the model that should be used, in the form of a string
      • alpaca.7B
      • alpaca.13B
      • llama.7B
      • llama.13B
      • llama.30B
      • llama.65B
    • id: the request ID (defaut is '0')
    • n_predict: the number of tokens to return (default is 128)
    • repeat_last_n: default is 64
    • repeat_penalty: default is 1.3
    • seed: the seed (default is -1)
    • temp: the temperature of the request (default is 0.5)
    • threads: the number of threads to use (default is 4)
    • top_k: default is 40
    • top_p: default is 0.9
  • request() - model.request(prompt)

    • prompt: (required) the prompt string
    • prettify: whether or not to clean and output just the string, or the whole request dictionary (default is True)

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A Python Wrapper for Dalai

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