Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Tapashh/Chess with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tapashh/Chess with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Tapashh/Chess") 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("Tapashh/Chess") model = AutoModelForImageClassification.from_pretrained("Tapashh/Chess", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0d9338683e325493a13973979497a058b3fcd7723d86e08e6a424d48adc7696
- Size of remote file:
- 4.86 kB
- SHA256:
- 615726dac38e2a8ebed81add35528e365935a6e5acb7ee3cd8281ca37fa785fa
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