Instructions to use rishabhjain16/whisper_base_to_pf10h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rishabhjain16/whisper_base_to_pf10h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rishabhjain16/whisper_base_to_pf10h")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("rishabhjain16/whisper_base_to_pf10h") model = AutoModelForSpeechSeq2Seq.from_pretrained("rishabhjain16/whisper_base_to_pf10h") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 146188dfc370cd1cc68c251dcabf459f1857b59e94d275c99ec86b3f30f9555c
- Size of remote file:
- 3.64 kB
- SHA256:
- 307aa50dc17bf16e87ecf8334ff70886eb5b11e308e4119168c1e4d77266b038
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