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:
- 1f58cba1d67c68db6979abf628a7a6b6d7907606e74e5b1c6b624aa2dbf17664
- Size of remote file:
- 967 MB
- SHA256:
- 6412ab0b63845c764c6eb8a9c86bd92518cd9f98695d342206dea155a7b8d658
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