Instructions to use Chars/DeepDanbooruClip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chars/DeepDanbooruClip with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Chars/DeepDanbooruClip") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("Chars/DeepDanbooruClip") model = AutoModelForZeroShotImageClassification.from_pretrained("Chars/DeepDanbooruClip", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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Frok from https://huggingface.co/OysterQAQ/DanbooruCLIP
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---
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tags:
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- vision
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widget:
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- src: https://huggingface.co/Chars/DeepDanbooruClip/resolve/main/example.jpg
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candidate_labels: Azur Lane, 3 girl with sword, cat ear, a dog
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example_title: Azur Lane
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- src: https://huggingface.co/Chars/DeepDanbooruClip/resolve/main/example2.jpg
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candidate_labels: 1 girl with black hair, rabbit ear, big breasts, minato aqua, fate/extra, k-on!, daiyousei, cirno
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example_title: cirno & daiyousei
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---
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Frok from https://huggingface.co/OysterQAQ/DanbooruCLIP
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