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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c6527592f2d93889b0e4430476a8c428bad57c5ac19c69bc9eff9bac8adc7d3
- Size of remote file:
- 967 MB
- SHA256:
- 6d2b1cc94969de9ecb84270f80dc6f018c01185fb0346c6568f9900334b809ce
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