Instructions to use cportoca/Quechua_Project_Whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cportoca/Quechua_Project_Whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cportoca/Quechua_Project_Whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cportoca/Quechua_Project_Whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("cportoca/Quechua_Project_Whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b1ca47976513296bb37c06d863b245538f8e1439e3c50a110f4558748bcec4a
- Size of remote file:
- 5.43 kB
- SHA256:
- 36949c22c441d5acd599d7115b4a394ea6df3d00fc2b09b4f28c24aa2fcebbb1
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