Comments (3)
from ao.
SDPA is a purely functional op so in if you pass in the existing parameters from the trained model you should not have to retrain.
from ao.
I'm going to close the issue since its not related to the torchao repository feel free to continue the discussion in the pytorch forums or in an issue in the pytorch repo
from ao.
Related Issues (18)
- Sparsity OSS colab tracker
- [Tracker] WIP Features for torchao v0.2
- 2:4 sparsity + PTQ(int8) model's inference HOT 7
- Custom CUDA extensions
- [RFC] Plans for sparsity HOT 2
- [RFC] More general affine quantization primitives HOT 1
- [Tracker] Outstanding Issues and WIP Features for version 0.1 HOT 2
- Reconsider using class method for Int8DynamicallyQuantizedLinearWeight.from_float HOT 1
- Project implicitly depends on torch nightly HOT 4
- Handle NonDynamicallyQuantizableLinear in smoothquant module HOT 2
- how do you implement int8 mm on cuda? HOT 1
- [RFC] Plans for torchao HOT 21
- apply_dynamic_quant for vit_b_16 HOT 2
- [New Feature] CUTLASS kernels for w4a8 quantization HOT 4
- [Tracker] General feature requests for torchao HOT 1
- 1 bit LLM implementation HOT 1
- [RFC] Plans for LLM QAT
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from ao.