
scikit-llm
Seamlessly integrate LLMs into scikit-learn.
Stars: 3398

Scikit-LLM is a tool that seamlessly integrates powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks. It allows users to leverage large language models for various text analysis applications within the familiar scikit-learn framework. The tool simplifies the process of incorporating advanced language processing capabilities into machine learning pipelines, enabling users to benefit from the latest advancements in natural language processing.
README:
Seamlessly integrate powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.
pip install scikit-llm
You can support the project in the following ways:
- β Star Scikit-LLM on GitHub (click the star button in the top right corner)
- π‘ Provide your feedback or propose ideas in the issues section or Discord
- π° Post about Scikit-LLM on LinkedIn or other platforms
- π Check out our other projects: Dingo, Falcon
Quick start example of zero-shot text classification using GPT:
# Import the necessary modules
from skllm.datasets import get_classification_dataset
from skllm.config import SKLLMConfig
from skllm.models.gpt.classification.zero_shot import ZeroShotGPTClassifier
# Configure the credentials
SKLLMConfig.set_openai_key("<YOUR_KEY>")
SKLLMConfig.set_openai_org("<YOUR_ORGANIZATION_ID>")
# Load a demo dataset
X, y = get_classification_dataset() # labels: positive, negative, neutral
# Initialize the model and make the predictions
clf = ZeroShotGPTClassifier(model="gpt-4")
clf.fit(X,y)
clf.predict(X)
For more information please refer to the documentation.
You can cite Scikit-LLM using the following BibTeX:
@software{ScikitLLM,
author = {Iryna Kondrashchenko and Oleh Kostromin},
year = {2023},
publisher = {beastbyte.ai},
address = {Linz, Austria},
title = {Scikit-LLM: Scikit-Learn Meets Large Language Models},
url = {https://github.com/iryna-kondr/scikit-llm }
}
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