Instructions to use Ali116/wav2vec2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ali116/wav2vec2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Ali116/wav2vec2-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Ali116/wav2vec2-base") model = AutoModelForAudioClassification.from_pretrained("Ali116/wav2vec2-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ali116/wav2vec2-base: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Ali116/wav2vec2-base/resolve/main/training_args.bin
- Command line
-
hf download hf://Ali116/wav2vec2-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ali116/wav2vec2-base/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 67c902e7e730d7dc7a858d7711ac2b74a1013202b0afefb1d0b62ff824c35f32
- Size of remote file:
- 4.09 kB
- SHA256:
- 6d1f0421dd965c999551c444fb57cd536cd2dcc13058e81ee3cd7c3db0d87ec5
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