Instructions to use seemdog/ManWav with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seemdog/ManWav with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seemdog/ManWav")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("seemdog/ManWav") model = AutoModelForCTC.from_pretrained("seemdog/ManWav", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f9bcaf073cf5c6a1ab4fb11d570e6d8c040c5191c2009131634b10286529d2f
- Size of remote file:
- 2.49 GB
- SHA256:
- f49d092e4fbe9a6dd9d2ec827a157394b49e9a716befd55fea70099799ff3e1e
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