Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use arpanl/Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arpanl/Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="arpanl/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("arpanl/Model") model = AutoModelForImageClassification.from_pretrained("arpanl/Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from arpanl/Model: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/arpanl/Model/resolve/main/training_args.bin
- Command line
-
hf download hf://arpanl/Model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/arpanl/Model/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- c5c72ae35be198420d60e0efd920180de89b2872db06d26ab32f6b38b0849a2a
- Size of remote file:
- 4.98 kB
- SHA256:
- e3908d5c733eb4947919dc2d992cf34178e68045538e3bb37d69b69794607888
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