Instructions to use Mahmoud1816Yasser/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud1816Yasser/tmp_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Mahmoud1816Yasser/tmp_trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Mahmoud1816Yasser/tmp_trainer") model = AutoModelForAudioClassification.from_pretrained("Mahmoud1816Yasser/tmp_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mahmoud1816Yasser/tmp_trainer: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Mahmoud1816Yasser/tmp_trainer/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mahmoud1816Yasser/tmp_trainer/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mahmoud1816Yasser/tmp_trainer/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- a319c489ee2d5f6fe1de1e59fbcbb007058b9616240dc5b2648c6f38887f608d
- Size of remote file:
- 378 MB
- SHA256:
- 47beecffa41f5ae8ed15677c196e4e8859b50d567f80e5f6d749f8f96971c8f0
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