Instructions to use walton98/model_out4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use walton98/model_out4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="walton98/model_out4")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("walton98/model_out4") model = AutoModelForAudioClassification.from_pretrained("walton98/model_out4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from walton98/model_out4: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/walton98/model_out4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://walton98/model_out4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/walton98/model_out4/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- cb2accd94e415f05fb525b20c9dd2b2c7db2ccc178711ad8389095d9a4b6465a
- Size of remote file:
- 378 MB
- SHA256:
- 46c20e4094f29f454e7dc19fa548ecc7eba65a2c8a7999b203d0c7117da993b5
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