Instructions to use Ramnathan/wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ramnathan/wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Ramnathan/wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Ramnathan/wav2vec2") model = AutoModelForCTC.from_pretrained("Ramnathan/wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ramnathan/wav2vec2: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/Ramnathan/wav2vec2/resolve/main/training_args.bin
- Command line
-
hf download hf://Ramnathan/wav2vec2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ramnathan/wav2vec2/resolve/main/training_args.bin
2.67 kB
- Xet hash:
- 54d76d04d4a2918f493e75c4b1bf9813ef7245a330a7f83e4496563e238b10e8
- Size of remote file:
- 2.67 kB
- SHA256:
- 2574ca9cec250c8e422317f3e5b407d62bfa4723e0366ca9746fd44c8ada5900
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