Instructions to use LanguageBind/LanguageBind_Audio_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LanguageBind/LanguageBind_Audio_FT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="LanguageBind/LanguageBind_Audio_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_Audio_FT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 598debc48e6876ca6d43c26f18c1aec7b8a77b7553f45c853ae105bc7ab0b292
- Size of remote file:
- 1.71 GB
- SHA256:
- b0fbb6a2703c1021d754262b5dde79e69f83b0b53763d327366e4d93efa15253
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