Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use sakethchalla/my_isl_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sakethchalla/my_isl_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sakethchalla/my_isl_model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sakethchalla/my_isl_model") model = AutoModelForImageClassification.from_pretrained("sakethchalla/my_isl_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sakethchalla/my_isl_model: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/sakethchalla/my_isl_model/resolve/main/training_args.bin
- Command line
-
hf download hf://sakethchalla/my_isl_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sakethchalla/my_isl_model/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- cef7a6da7b26e741e8485898b1717359cc7771f03993e6cc7b1b9dd2c5f55d86
- Size of remote file:
- 3.58 kB
- SHA256:
- dd626427ad16c7c43dbf37df35c63de7fceb175b66787cc4cb9aafbd21609d9a
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