| microsoft/nni |
13,536 |
|
8 |
27 |
over 2 years ago |
55 |
September 14, 2023 |
342 |
mit |
Python |
| An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. |
| 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. |
| cnkuangshi/LightCTR |
599 |
|
0 |
0 |
almost 7 years ago |
0 |
|
1 |
apache-2.0 |
C++ |
| Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Parameter Server and Ring-AllReduce collective communication. |
| SforAiDl/KD_Lib |
476 |
|
0 |
0 |
about 3 years ago |
8 |
May 18, 2022 |
18 |
mit |
Python |
| A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization. |
| microsoft/archai |
428 |
|
0 |
0 |
over 2 years ago |
9 |
September 15, 2023 |
2 |
mit |
Python |
| Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research. |
| cedrickchee/awesome-ml-model-compression |
378 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
|
| Awesome machine learning model compression research papers, tools, and learning material. |
| vinhkhuc/JFastText |
215 |
|
8 |
3 |
almost 3 years ago |
5 |
May 29, 2023 |
46 |
other |
Java |
| Java interface for fastText |
| 1duo/awesome-ai-infrastructures |
171 |
|
0 |
0 |
almost 7 years ago |
0 |
|
0 |
|
|
| Infrastructures™ for Machine Learning Training/Inference in Production. |
| DwangoMediaVillage/keras_compressor |
152 |
|
0 |
0 |
almost 7 years ago |
0 |
|
11 |
|
Python |
| Model Compression CLI Tool for Keras. |
| jim-schwoebel/allie |
126 |
|
0 |
0 |
over 2 years ago |
0 |
|
70 |
apache-2.0 |
Python |
| 🤖 An automated machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers). Python 3.6 required. |
