Instructions to use hf-internal-testing/tiny-random-SiglipForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SiglipForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-SiglipForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SiglipForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-SiglipForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-SiglipForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 118 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-SiglipForImageClassification/resolve/refs%2Fpr%2F50/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-SiglipForImageClassification@refs/pr/50/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-SiglipForImageClassification/resolve/refs%2Fpr%2F50/model.safetensors
118 kB
- Xet hash:
- e4fce0ddaa6da9a266bff236018ff86365f9a9e8f53a449184c8fadf33a2eb80
- Size of remote file:
- 118 kB
- SHA256:
- 42f83d81f0297741f4fe617c938c2b5af2c571b5750fefe6e741e9b38c2095ae
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