Automatic Speech Recognition
Transformers
PyTorch
JAX
Telugu
whisper
whisper-event
Eval Results (legacy)
Instructions to use vasista22/whisper-telugu-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vasista22/whisper-telugu-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vasista22/whisper-telugu-large-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vasista22/whisper-telugu-large-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("vasista22/whisper-telugu-large-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d5fa5427ef06f639ed7ec0efae901ff292c7a3ab2912f89d6bbadd7e563b457
- Size of remote file:
- 6.17 GB
- SHA256:
- 800dadaa90f2431b83f8e18f8e80a92933e32db9f0153db88e26bb709eebc93e
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