Instructions to use varunril/lan_det with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varunril/lan_det with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="varunril/lan_det")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("varunril/lan_det") model = AutoModelForAudioClassification.from_pretrained("varunril/lan_det", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from varunril/lan_det: direct link, hf CLI and curl.
- Browser
- Download file 615 MB
-
https://huggingface.co/varunril/lan_det/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://varunril/lan_det/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/varunril/lan_det/resolve/main/pytorch_model.bin
615 MB
- Xet hash:
- 4d7fbaea0880f135cd33b864030dfe788869f63221779478c968428a7f4457c6
- Size of remote file:
- 615 MB
- SHA256:
- 6ded31e35036a85fe27b810198c6f9dd332d8b506df244c156b3af8524a01bce
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