Instructions to use fdgf65/Testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use fdgf65/Testing with timm:
import timm model = timm.create_model("hf_hub:fdgf65/Testing", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e183359ab8759afb51124d41dc4170531df43591f3b8fab0aad46f4b706bcf81
- Size of remote file:
- 6.18 MB
- SHA256:
- b60ec172c740ffe10aecd988335a1f9f67d3eada602e7e03f8d5b5f86289d894
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.