Instructions to use arpanl/finetuned_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arpanl/finetuned_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="arpanl/finetuned_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/finetuned_model") model = AutoModelForImageClassification.from_pretrained("arpanl/finetuned_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from arpanl/finetuned_model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/arpanl/finetuned_model/resolve/main/training_args.bin
- Command line
-
hf download hf://arpanl/finetuned_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/arpanl/finetuned_model/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 0b167ce55d3560cea6a0b0f4d322b622ee6226db20401d2d8924110b2ffe7a7c
- Size of remote file:
- 4.92 kB
- SHA256:
- d9ebd1738b6110bbc356c703dbf70f3a51db7b7345a45cdf7ec6c4380409712a
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