Instructions to use peft-internal-testing/tiny-random-ResNetForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-random-ResNetForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="peft-internal-testing/tiny-random-ResNetForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("peft-internal-testing/tiny-random-ResNetForImageClassification") model = AutoModelForImageClassification.from_pretrained("peft-internal-testing/tiny-random-ResNetForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c29f586477b4add5aa164172c302029e2139ff65b81d4dad47dd1a881129412
- Size of remote file:
- 84.9 kB
- SHA256:
- b42df6c88db1b4ceba9504f335e9bcd0eba87aca6276260bdbb41011abb8c2cf
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