Metadata-Version: 2.1
Name: localcat
Version: 0.0.9
Summary: Fine-tune Large Language Models locally.
Author-email: Ewen Wang <wang.enqun@outlook.com>
License: MIT License
        
        Copyright (c) 2024 Ewen Wang
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/Ewen2015/LocalCat
Project-URL: Documentation, https://localcat.readthedocs.io
Project-URL: Repository, https://github.com/Ewen2015/LocalCat.git
Project-URL: Issues, https://github.com/Ewen2015/LocalCat/issues
Keywords: llm,finetune,ai,aws
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: torch >=2.0
Requires-Dist: transformers ==4.30.2
Requires-Dist: datasets ==2.16.1
Requires-Dist: sentencepiece ==0.1.99
Requires-Dist: pydantic ==1.10.8
Requires-Dist: evaluate ==0.4.1
Requires-Dist: accelerate ==0.26.1
Requires-Dist: sacrebleu ==2.4.0
Requires-Dist: nltk ==3.8.1
Requires-Dist: tqdm ==4.64.1
Requires-Dist: boto3 ==1.34.38
Requires-Dist: sagemaker ==2.207.1

# LocalCat

![PyPI version](https://badge.fury.io/py/localcat.svg)
![Documentation Status](https://readthedocs.org/projects/localcat/badge/?version=latest)
![Python Versions](https://img.shields.io/pypi/pyversions/localcat.svg)
![GitHub](https://img.shields.io/github/license/ewen2015/localcat)

**LocalCat** is designed to make the LLM strategy easy to implement. It provides a simple API and an intuitive interface for loading, fine-tuning, and deploying large deep learning models. With LocalCat, you can easily fine-tune pre-trained models on your own data and leverage their power for your specific tasks.

## Tasks
### Translation
LocalCat offers user-friendly tools for translation tasks, allowing the translator to be deployed as an endpoint or for batch processing of dataframes. Additionally, it provides fine-tuning capabilities for local deployment. 

LocalCat's intuitive interface and efficient processing make it a valuable asset for any translation project. With its advanced features and customizable options, users can easily tailor their translations to meet specific requirements and ensure accuracy. Whether you're working on a small document or a large dataset, LocalCat has the tools you need to streamline the translation process and achieve high-quality results.

### Chat
#### Retrieval Augmented Generation (RAG)
Localcat specializes in open-source LLMs and RAG for local deployment. Localcat offers a wide range of solutions for local deployment, including custom configurations and expert support for seamless integration. With a focus on user-friendly interfaces and scalable performance, Localcat is the ideal choice for organizations looking to optimize their LLMs and RAG processes.

## Install
```python
pip install localcat
```
