Instructions to use razhan/whisper-base-me with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razhan/whisper-base-me with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="razhan/whisper-base-me")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("razhan/whisper-base-me") model = AutoModelForSpeechSeq2Seq.from_pretrained("razhan/whisper-base-me", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8eb216b284691f500651cddf74e42643e4eb43e18beb866b22eccd3fc2addbc
- Size of remote file:
- 5.5 kB
- SHA256:
- 0b21dd2fbb6f48b702acebf8eb53a2a0b19a5c2b1199a44755bdc62c5b8912ba
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