Instructions to use Jialuo21/SciScore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jialuo21/SciScore with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Jialuo21/SciScore") 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("Jialuo21/SciScore") model = AutoModelForZeroShotImageClassification.from_pretrained("Jialuo21/SciScore", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download teaser.png from Jialuo21/SciScore: direct link, hf CLI and curl.
- Browser
- Download file 22 MB
-
https://huggingface.co/Jialuo21/SciScore/resolve/main/teaser.png
- Command line
-
hf download hf://Jialuo21/SciScore/teaser.png
-
curl -L -o teaser.png https://huggingface.co/Jialuo21/SciScore/resolve/main/teaser.png
22 MB
- Xet hash:
- 627e9274921bb05763d92afc2c4fbffbf8a46aeeb596e780843a666dc1ca5bed
- Size of remote file:
- 22 MB
- SHA256:
- 3532dac6f4bffbadbe7d6097890efd532451ca28c7df5627924546cdeb52f13f
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