Instructions to use hf-internal-testing/tiny-random-BeitForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BeitForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-BeitForImageClassification") 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-BeitForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-BeitForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-BeitForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 119 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-BeitForImageClassification/resolve/refs%2Fpr%2F3/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-BeitForImageClassification@refs/pr/3/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-BeitForImageClassification/resolve/refs%2Fpr%2F3/model.safetensors
119 kB
- Xet hash:
- b40066f29706b0c61aba2ca30d313a015c97b53a07c86a43bbc53aad51aa0a13
- Size of remote file:
- 119 kB
- SHA256:
- 822089b2c3d6d9b92a9b55a430c4e85ce5ef098cd224fd117174901b8657949e
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