Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use sakethchalla/isl-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sakethchalla/isl-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sakethchalla/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/isl-model") model = AutoModelForImageClassification.from_pretrained("sakethchalla/isl-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sakethchalla/isl-model: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/sakethchalla/isl-model/resolve/main/training_args.bin
- Command line
-
hf download hf://sakethchalla/isl-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sakethchalla/isl-model/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 15a721fd23ceb0e2bcea32ac1a48bfcdf8ce9ccf61100d992781b5449a550ca0
- Size of remote file:
- 3.64 kB
- SHA256:
- c438e660c2c660f1aca4c664ecd7bc12206a8abca4bef4cf127249e1eaf46394
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