Instructions to use van-ng/intent_classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use van-ng/intent_classify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="van-ng/intent_classify")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("van-ng/intent_classify") model = AutoModelForAudioClassification.from_pretrained("van-ng/intent_classify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from van-ng/intent_classify: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/van-ng/intent_classify/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://van-ng/intent_classify@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/van-ng/intent_classify/resolve/refs%2Fpr%2F1/pytorch_model.bin
378 MB
- Xet hash:
- 0a183bf6fbb96989517f0edabc19b0a01300beaacc1e6ca65918151c449fb067
- Size of remote file:
- 378 MB
- SHA256:
- d6d3346bcf76b6ca3a3d544e9eda8085994e8c7967a4e86441edb9ac34ada85f
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