Instructions to use hf-internal-testing/tiny-random-DeiTForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DeiTForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-DeiTForImageClassification") 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("hf-internal-testing/tiny-random-DeiTForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-DeiTForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5323c040a8f681426f2d634f640a14462de26c8384608b440ac3ad551c5cced
- Size of remote file:
- 177 kB
- SHA256:
- 62a5d51f43cb59319e37f2d0c4d429e784e41b2d8b4d554c4a6d53bfcbd28739
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