Instructions to use LanguageBind/LanguageBind_Video_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LanguageBind/LanguageBind_Video_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_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_FT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 924bbf6fac636fdcc3b08324d16887c7369f70fee1a3f738f9aa63bd38f99601
- Size of remote file:
- 2.11 GB
- SHA256:
- c0ddf4a2e555e8c5174b67764ea7077269207cf49c78ddae8a2f8bb4622a86cb
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