Image Classification
timm
PyTorch
Safetensors
vision-transformer
swin
gravitational-lensing
strong-lensing
astronomy
astrophysics
Eval Results (legacy)
Instructions to use parlange/swin-gravit-a1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use parlange/swin-gravit-a1 with timm:
import timm model = timm.create_model("hf_hub:parlange/swin-gravit-a1", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41044404cedf0faf1ba7418c1a4c737eb346c2c588f336d02460ae25cfa46264
- Size of remote file:
- 347 MB
- SHA256:
- ce878346ef57c52462dad34cd9326bbc66a680ec0cb9dace4bb35212f0c1e4f3
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