Instructions to use hf-tiny-model-private/tiny-random-BeitForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BeitForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/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-tiny-model-private/tiny-random-BeitForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-BeitForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-BeitForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 119 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-BeitForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-BeitForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-BeitForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
119 kB
- Xet hash:
- 0141f2f153d9f7d69ec8569f2117a2f0f12cdae2a8fb56c85ed57f4d5000b03b
- Size of remote file:
- 119 kB
- SHA256:
- 6e2133a501e284403fae0c6ac96fbc364d424b433196a8b12959fe9fc74ec475
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