Instructions to use hf-internal-testing/tiny-random-CLIPForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CLIPForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-CLIPForImageClassification") 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-CLIPForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-CLIPForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-CLIPForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 90.1 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-CLIPForImageClassification/resolve/refs%2Fpr%2F20/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-CLIPForImageClassification@refs/pr/20/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-CLIPForImageClassification/resolve/refs%2Fpr%2F20/model.safetensors
90.1 kB
- Xet hash:
- 61f6ddc0c911325cf6ad10fce331fe8873ba1ea11ba40c2af01b5e4946872205
- Size of remote file:
- 90.1 kB
- SHA256:
- 101bfffbfb967a27d0c30460a704889397889aacbbd34729bf67c6fb89589cbd
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