Audio Classification
Transformers
TensorBoard
Safetensors
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use iamhack/DH_ONM_WORDS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamhack/DH_ONM_WORDS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="iamhack/DH_ONM_WORDS")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("iamhack/DH_ONM_WORDS") model = AutoModelForAudioClassification.from_pretrained("iamhack/DH_ONM_WORDS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from iamhack/DH_ONM_WORDS: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/iamhack/DH_ONM_WORDS/resolve/main/training_args.bin
- Command line
-
hf download hf://iamhack/DH_ONM_WORDS/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/iamhack/DH_ONM_WORDS/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- e6dc1bb6efb40c2ccc01b5a8b0c3ed6bde15dcd8dacbca5d096c8ada9ef2d8ca
- Size of remote file:
- 4.22 kB
- SHA256:
- 53f1edf6ce2d27bd0e413921fc89f06f69fc40aa579792c5688782e4b4e59f76
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