Instructions to use manuth/wer7_augPitch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manuth/wer7_augPitch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="manuth/wer7_augPitch")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("manuth/wer7_augPitch") model = AutoModelForSpeechSeq2Seq.from_pretrained("manuth/wer7_augPitch") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ec116491252358968ec5fe23577d8ba83dd88df21532991911abc4a62ffc4b2
- Size of remote file:
- 5.56 kB
- SHA256:
- 5e847fe1a021162b3e7f10a56e403ea0708b6c8ffd8bdab346f2388a80db5238
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