Instructions to use mlengineer-ai/whisper-small-fa-specaug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlengineer-ai/whisper-small-fa-specaug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mlengineer-ai/whisper-small-fa-specaug")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mlengineer-ai/whisper-small-fa-specaug") model = AutoModelForSpeechSeq2Seq.from_pretrained("mlengineer-ai/whisper-small-fa-specaug") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d2e58a7a21eb03895b0ca04cd1cea5ddfd2753ee4f6e46abc3bf4998856eb52
- Size of remote file:
- 967 MB
- SHA256:
- 0a9548c887e24b061df453d098b45e4af91947e8209e55e5f7c4b1ee73b749bd
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