Instructions to use LanguageBind/LanguageBind_Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LanguageBind/LanguageBind_Video with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="LanguageBind/LanguageBind_Video") 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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fdcb60ba9d81aa46d5eed62c195c97a6338684b32ff3177a7811eca79e40a1a
- Size of remote file:
- 2.13 GB
- SHA256:
- a1eab238ed8d6b45d35389a54fb411f4a0a606afeb5098f61319b32a1e8a0af1
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