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 exp.png from Jialuo21/SciScore: direct link, hf CLI and curl.
- Browser
- Download file 209 kB
-
https://huggingface.co/Jialuo21/SciScore/resolve/main/exp.png
- Command line
-
hf download hf://Jialuo21/SciScore/exp.png
-
curl -L -o exp.png https://huggingface.co/Jialuo21/SciScore/resolve/main/exp.png
209 kB

- Xet hash:
- 1ca38c096c52d3ce6f310cad7e1c6343a48ad7f51cbc52506b859ffb8a21db27
- Size of remote file:
- 209 kB
- SHA256:
- da473dfa63a827e3a4e5a47dd2409b3f1d981cee2c684197ffdee14bde6b5985
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