Instructions to use LanguageBind/LanguageBind_Video_V1.5_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LanguageBind/LanguageBind_Video_V1.5_FT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="LanguageBind/LanguageBind_Video_V1.5_FT") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModelForZeroShotImageClassification model = AutoModelForZeroShotImageClassification.from_pretrained("LanguageBind/LanguageBind_Video_V1.5_FT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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license: mit
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license: mit
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datasets:
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- fka/awesome-chatgpt-prompts
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- HuggingFaceH4/ultrachat_200k
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language:
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- aa
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metrics:
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- accuracy
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pipeline_tag: text-classification
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