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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-DeiTForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 177 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-DeiTForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-DeiTForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-DeiTForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
177 kB
- Xet hash:
- a5323c040a8f681426f2d634f640a14462de26c8384608b440ac3ad551c5cced
- Size of remote file:
- 177 kB
- SHA256:
- 62a5d51f43cb59319e37f2d0c4d429e784e41b2d8b4d554c4a6d53bfcbd28739
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