Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use GGital/vit-Covid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GGital/vit-Covid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="GGital/vit-Covid") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("GGital/vit-Covid") model = AutoModelForImageClassification.from_pretrained("GGital/vit-Covid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ed82b22abc0a5d32d9cd665b3fb4bbad934b8094cdf4bada85ea0e258c9789e
- Size of remote file:
- 343 MB
- SHA256:
- 72904eec0e99092000be6b4913108daecea58a65df9cbbb6bbfc557ef522c71f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.