pygptj 2.0.3

Python bindings for the GGML GPT-J Laguage model

PyGPT-J

• Python bindings for GPT-J ggml language models.
• Almost the same API as pyllamacpp.

Table of contents

• Installation
• CLI
• Tutorial
  • Quick start
  • Interactive Dialogue
  • Attribute a persona to the language model
• API reference
• License

Installation

1. The easy way is to use the prebuilt wheels

pip install pygptj

2. Build from source:

git clone git+https://github.com/abdeladim-s/pygptj.git

CLI

You can run the following simple command line interface to test the package once it is installed:

pygtj path/to/ggml/model

Tutorial

Quick start

from pygptj.model import Model

model = Model(model_path='path/to/gptj/ggml/model')
for token in model.generate("Tell me a joke ?"):
    print(token, end='', flush=True)

Interactive Dialogue

You can set up an interactive dialogue by simply keeping the model variable alive:

from pygptj.model import Model

model = Model(model_path='/path/to/ggml/model')
while True:
    try:
        prompt = input("You: ", flush=True)
        if prompt == '':
            continue
        print(f"AI:", end='')
        for token in model.generate(prompt):
            print(f"{token}", end='', flush=True)
        print()
    except KeyboardInterrupt:
        break

Attribute a persona to the language model

The following is an example showing how to "attribute a persona to the language model" :

from pygptj.model import Model

prompt_context = """Act as Bob. Bob is helpful, kind, honest,
and never fails to answer the User's requests immediately and with precision. 

User: Nice to meet you Bob!
Bob: Welcome! I'm here to assist you with anything you need. What can I do for you today?
"""

prompt_prefix = "\nUser:"
prompt_suffix = "\nBob:"

model = Model(model_path='/path/to/ggml/model',
              prompt_context=prompt_context,
              prompt_prefix=prompt_prefix,
              prompt_suffix=prompt_suffix)

while True:
  try:
    prompt = input("User: ")
    if prompt == '':
      continue
    print(f"Bob: ", end='')
    for token in model.generate(prompt, antiprompt='User:'):
      print(f"{token}", end='', flush=True)
      print()
  except KeyboardInterrupt:
    break

• You can always refer to the short documentation for more details.

API reference

You can check the API reference documentation for more details.

License

This project is licensed under the MIT License.