Instructions to use hf-tiny-model-private/tiny-random-AltCLIPModel 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-AltCLIPModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="hf-tiny-model-private/tiny-random-AltCLIPModel") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-AltCLIPModel") model = AutoModelForZeroShotImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-AltCLIPModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-AltCLIPModel: direct link, hf CLI and curl.
- Browser
- Download file 548 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-AltCLIPModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-AltCLIPModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-AltCLIPModel/resolve/refs%2Fpr%2F1/model.safetensors
548 kB
- Xet hash:
- 102b0c126e8fb2b389f251b4067667d7923967ea698b09683e0bdb0bb7516f23
- Size of remote file:
- 548 kB
- SHA256:
- 802b4aaad21315de481a392143b0895b028fd6eabe2acb9bb4cc6bd335c5044e
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