Instructions to use arpanl/Fine-Tuned_Model3_Transfer_learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arpanl/Fine-Tuned_Model3_Transfer_learning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="arpanl/Fine-Tuned_Model3_Transfer_learning") 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/Fine-Tuned_Model3_Transfer_learning") model = AutoModelForImageClassification.from_pretrained("arpanl/Fine-Tuned_Model3_Transfer_learning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from arpanl/Fine-Tuned_Model3_Transfer_learning: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/arpanl/Fine-Tuned_Model3_Transfer_learning/resolve/main/training_args.bin
- Command line
-
hf download hf://arpanl/Fine-Tuned_Model3_Transfer_learning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/arpanl/Fine-Tuned_Model3_Transfer_learning/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- 3c5c91382fcf9d489f3a0c3f5a44aaecb1a0969c7dd66a2337fff9df8e2df0f9
- Size of remote file:
- 4.79 kB
- SHA256:
- d53fc00bdd7ecc50b26e9869c95e2246ee9cb99c018dfd6942a5d93c5c83a62a
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