| Name | Version | Summary | date |
| fmo-core |
0.9 |
Model Optimizer for Friendli Engine. |
2025-01-03 08:40:30 |
| autoawq-kernels |
0.0.9 |
AutoAWQ Kernels implements the AWQ kernels. |
2024-11-16 15:42:59 |
| optimum-quanto |
0.2.6 |
A pytorch quantization backend for optimum. |
2024-10-29 17:13:31 |
| owlite |
0.0.8 |
A fake package to warn the user they are not installing the correct package. |
2024-10-02 07:36:45 |
| hquant |
0.1.0 |
High quality quantization for Pillow images. |
2024-09-19 23:02:03 |
| bitlinear-pytorch |
0.5.0 |
Implementation of the BitLinear layer from: The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits |
2024-09-11 15:26:31 |
| awq-cli |
0.2.0 |
Command-line interface for AutoAWQ |
2024-08-09 08:02:27 |
| sparsezoo |
1.8.1 |
Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes |
2024-07-19 16:25:22 |
| sparseml-nightly |
1.8.0.20240630 |
Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models |
2024-06-30 20:38:38 |
| sparseml |
1.8.0 |
Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models |
2024-06-21 15:53:30 |
| quanto |
0.2.0 |
A quantization toolkit for pytorch. |
2024-05-24 10:49:08 |
| grag |
0.0.1 |
A simple package for implementing RAG |
2024-05-09 21:21:22 |
| sparsezoo-nightly |
1.8.0.20240506 |
Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes |
2024-05-06 19:37:51 |