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:
- 75a8125fe62d9d441df52940305d627932c1573a65558a07d68f9b00e168e628
- Size of remote file:
- 347 MB
- SHA256:
- 36f66121d3f0b87883695794cfbc00cad9fe7cd387573ce637cd5aebff76e39f
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