iryna-kondr/scikit-llm
Fork: 273 Star: 3354 (更新于 2024-10-29 20:05:03)
license: MIT
Language: Python .
Seamlessly integrate LLMs into scikit-learn.
最后发布版本: v1.4.0 ( 2024-08-05 04:11:49)
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: Dingo, Falcon
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 }
}
最近版本更新:(数据更新于 2024-10-06 09:27:02)
2024-08-05 04:11:49 v1.4.0
2024-07-25 03:12:25 v1.3.1
2024-07-07 05:35:32 v1.3.0
2024-06-26 02:04:31 v1.2.0
2024-05-25 16:26:32 v1.1.0
2023-12-26 02:09:28 v1.0.0
2023-11-09 19:22:13 v0.4.2
2023-08-24 16:36:07 v0.4.1
2023-08-24 03:09:25 v0.4.0
2023-08-15 22:56:08 v0.3.4
主题(topics):
chatgpt, deep-learning, llm, machine-learning, scikit-learn, transformers
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