Awesome
<div align="center"> <img alt="logo" src="https://gist.githubusercontent.com/OKUA1/55e2fb9dd55673ec05281e0247de6202/raw/41063fcd620d9091662fc6473f9331a7651b4465/scikit-llm.svg" height = "250"> </div>Scikit-LLM: Scikit-Learn Meets Large Language Models
Seamlessly integrate powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.
Installation 💾
pip install scikit-llm
Support us 🤝
You can support the project in the following ways:
- ⭐ Star Scikit-LLM on GitHub (click the star button in the top right corner)
- 💡 Provide your feedback or propose ideas in the issues section or Discord
- 📰 Post about Scikit-LLM on LinkedIn or other platforms
- 🔗 Check out our other projects: <a href="https://github.com/beastbyteai/agent_dingo">Dingo</a>, <a href="https://github.com/beastbyteai/agent_dingo">Falcon</a>
Quick Start & Documentation 📚
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.
Citation
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 }
}