Instructions to use fiza12/trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fiza12/trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="fiza12/trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("fiza12/trainer") model = AutoModelForAudioClassification.from_pretrained("fiza12/trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fiza12/trainer: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/fiza12/trainer/resolve/main/training_args.bin
- Command line
-
hf download hf://fiza12/trainer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fiza12/trainer/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 15921a358904eb32e28069c29dc077bcdedbd05c6ef93c1271533cf7026cef16
- Size of remote file:
- 4.73 kB
- SHA256:
- 1a6c427bb1d3c26cf2c4c8d9c78cfd270ced9f99bfb347a6bbf123f411050ab5
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