Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Spanish
Catalan
whisper
bsc
projecte-aina
barcelona-supercomputing-center
whisper-large-v3
code-switching
spanish-catalan
spanish
catalan
Instructions to use projecte-aina/whisper-large-v3-tiny-caesar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use projecte-aina/whisper-large-v3-tiny-caesar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="projecte-aina/whisper-large-v3-tiny-caesar")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("projecte-aina/whisper-large-v3-tiny-caesar") model = AutoModelForSpeechSeq2Seq.from_pretrained("projecte-aina/whisper-large-v3-tiny-caesar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24b991db2791e7d395eebddd9618e90bf51fcf3f0c464791bb4c81c35915cd7d
- Size of remote file:
- 5.11 kB
- SHA256:
- 86d267c0aebf9c54b54396d07ac96bb6d1becc69e7fe777abbc08a0ebd162008
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