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efficient-transformers
efficient-transformers contient 3 skills collectées depuis quic, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Add, modify, or review QEfficient transform code. Use when the user wants a new PyTorch transform, module mapping, method mapper, module mutator, quantization transform, prefill/sampler/SPD/blocking transform, ONNX-adjacent transform wiring, or tests for transform registration/parity in `QEfficient/base/pytorch_transforms.py`, `QEfficient/transformers/models/pytorch_transforms.py`, `QEfficient/transformers/quantizers/quant_transforms.py`, `QEfficient/base/modeling_qeff.py`, or `QEfficient/transformers/models/modeling_auto.py`.
Add support for a new Hugging Face model in this QEfficient repo. Use when the user provides a Hub model id, pasted model card, config excerpt, or architecture name and wants the QEff equivalent implemented, mapped to the closest existing wrapper family, validated with a tiny or config-derived test model, and covered through `tests/test_model_quickcheck.py`.
Rebase downstream QEff wrappers onto Hugging Face Transformers mainline with minimal divergence, preserving runtime/export parity and validating against tests/test_model_quickcheck.py.