This release does not contain any new feature, but it is the first one with the new package name.
0.2.0
New features
- requantize helper by calmitchell617, - StableDiffusion example by thliang01, - improved linear backward path by dacorvo , - AWQ int4 kernels by dacorvo .
0.1.2
With this release, we enable Intel Neural Compressor v1.8 magnitude pruning for a variety of NLP tasks with the introduction of `IncTrainer` which handles the pruning process.
0.1.1
With this release, we enable Intel Neural Compressor v1.7 PyTorch dynamic, post-training and aware-training quantization for a variety of NLP tasks. This support includes the overall process, from quantization application to the loading of the resulting quantized model. The latter being enabled by the introduction of the `IncQuantizedModel` class.
0.1.0
New features
- group-wise quantization, - safe serialization.
0.0.13
New features
- new `QConv2d` quantized module, - official support for `float8` weights.
Bug fixes
- fix `QbitsTensor.to()` that was not moving the inner tensors, - prevent shallow `QTensor` copies when loading weights that do not move inner tensors.