Instructions to use stillerman/stammer-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stillerman/stammer-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="stillerman/stammer-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("stillerman/stammer-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("stillerman/stammer-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c48f487fe5b562f5c697e471f9395109d2fc91e71ed8d2e2aa4f53b9b38e5175
- Size of remote file:
- 5.24 kB
- SHA256:
- a49e5a621f444a81f7dd62fcc36a4d03fcc2c5cc9968c4e214ca502b03d6af2d
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