Instructions to use nateraw/test_model_a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/test_model_a with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nateraw/test_model_a") 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("nateraw/test_model_a") model = AutoModelForImageClassification.from_pretrained("nateraw/test_model_a", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nateraw/test_model_a: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/nateraw/test_model_a/resolve/main/training_args.bin
- Command line
-
hf download hf://nateraw/test_model_a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nateraw/test_model_a/resolve/main/training_args.bin
2.67 kB
- Xet hash:
- 92b8be4b030dbb5055429071e386c72ee178ec8d053e0c32cbd7f70d2806d614
- Size of remote file:
- 2.67 kB
- SHA256:
- a8c0b14169b4bec7ca8fb7355c98f7642b26b1a5a065cf9ae8201096e4c4271c
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