Instructions to use madoss/wav2vec-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madoss/wav2vec-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="madoss/wav2vec-finetuned")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("madoss/wav2vec-finetuned") model = AutoModelForCTC.from_pretrained("madoss/wav2vec-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46e541a87d0f42f19888cb648cf83333b7b6081e6f8cd1fcc501c12d013f686b
- Size of remote file:
- 5.33 kB
- SHA256:
- 0a84700d09c3c54ccbd546c8f490cc00de8007281749fe8977ade05a39c26ecf
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