| SYSTRAN/faster-whisper |
6,940 |
|
0 |
22 |
about 2 years ago |
12 |
November 26, 2023 |
140 |
mit |
Python |
| Faster Whisper transcription with CTranslate2 |
| UFund-Me/Qbot |
4,799 |
|
0 |
0 |
over 2 years ago |
0 |
|
51 |
mit |
Jupyter Notebook |
| [🔥updating ...] AI 自动量化交易机器人 AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant |
| AutoGPTQ/AutoGPTQ |
3,206 |
|
0 |
0 |
about 2 years ago |
0 |
|
174 |
mit |
Python |
| An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm. |
| IntelLabs/nlp-architect |
2,924 |
|
0 |
0 |
over 3 years ago |
10 |
April 12, 2020 |
14 |
apache-2.0 |
Python |
| A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks |
| Tencent/PocketFlow |
2,553 |
|
0 |
0 |
over 5 years ago |
0 |
|
73 |
other |
Python |
| An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications. |
| OpenNMT/CTranslate2 |
2,437 |
|
0 |
23 |
about 2 years ago |
103 |
December 05, 2023 |
110 |
mit |
C++ |
| Fast inference engine for Transformer models |
| dvmazur/mixtral-offloading |
1,943 |
|
0 |
0 |
about 2 years ago |
0 |
|
12 |
mit |
Python |
| Run Mixtral-8x7B models in Colab or consumer desktops |
| lucidrains/vector-quantize-pytorch |
1,627 |
|
0 |
25 |
about 2 years ago |
160 |
December 06, 2023 |
27 |
mit |
Python |
| Vector Quantization, in Pytorch |
| htqin/awesome-model-quantization |
1,449 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
|
|
| A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo. |
| tensorflow/model-optimization |
1,445 |
|
3 |
27 |
over 2 years ago |
30 |
May 26, 2023 |
207 |
apache-2.0 |
Python |
| A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning. |
