Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Tamil
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use eswardivi/whisper-small-ta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eswardivi/whisper-small-ta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eswardivi/whisper-small-ta")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("eswardivi/whisper-small-ta") model = AutoModelForSpeechSeq2Seq.from_pretrained("eswardivi/whisper-small-ta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab092b2d69729803a9cd558c07e2a0c25f06056a1ca42e0922c3c4944d099de7
- Size of remote file:
- 3.71 kB
- SHA256:
- 962920e625dad695bd1e12fe9637d42b4bb63c06976eb550d82a286afe0b403e
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