Image Classification
timm
PyTorch
Safetensors
vision-transformer
twins_pcpvt
gravitational-lensing
strong-lensing
astronomy
astrophysics
Eval Results (legacy)
Instructions to use parlange/twins_pcpvt-gravit-a2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use parlange/twins_pcpvt-gravit-a2 with timm:
import timm model = timm.create_model("hf_hub:parlange/twins_pcpvt-gravit-a2", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ece753e00d340499d861052d382e62f6a625fe13d31cdfa3633ef4fa22037db
- Size of remote file:
- 173 MB
- SHA256:
- 5017ae1cd60696c63c1f1770fac0bca9f3126886403392de7c7d81605bc4b7da
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