Image Classification
timm
PyTorch
vision-transformer
knowledge-distillation
feature-distillation
model-compression
interpretability
explainability
representation-analysis
encoding-mismatch
spectral-energy-pattern
spectral-kd
low-rank
pca
svd
deit-tiny
distilled-deit-tiny
cait-s24
lift
widelast
icml-2026
Eval Results (legacy)
Instructions to use Huiyuancs/Encoding_Mismatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Huiyuancs/Encoding_Mismatch with timm:
import timm model = timm.create_model("hf_hub:Huiyuancs/Encoding_Mismatch", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eacd937abd3927715eea9675f2c3ce873ef48cd5c33bb0f9980b16d26cd34d15
- Size of remote file:
- 2.64 MB
- SHA256:
- 65a65c01a4bf68c8f949dafa0185ffea1d609388ea5aa4be25abafbae1796ef8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.