Instructions to use ashm/test-docs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashm/test-docs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="ashm/test-docs") 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("ashm/test-docs") model = AutoModelForZeroShotImageClassification.from_pretrained("ashm/test-docs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ashm/test-docs: direct link, hf CLI and curl.
- Browser
- Download file 784 MB
-
https://huggingface.co/ashm/test-docs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ashm/test-docs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ashm/test-docs/resolve/main/pytorch_model.bin
784 MB
- Xet hash:
- e9078e22f010ee2cb983a3c776cebfc5b52d7d9a8f69eda5862ef45ece949e69
- Size of remote file:
- 784 MB
- SHA256:
- 8792dba76fc3a96544a87bb0f76c82167b4ba509d57c08b98b9c9266f764598b
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