Automatic Speech Recognition
Transformers
PyTorch
JAX
Kannada
whisper
whisper-event
Eval Results (legacy)
Instructions to use Imadsarvm/Sarvm-Translation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Imadsarvm/Sarvm-Translation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Imadsarvm/Sarvm-Translation")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Imadsarvm/Sarvm-Translation") model = AutoModelForSpeechSeq2Seq.from_pretrained("Imadsarvm/Sarvm-Translation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a60a5d6051d684e651864db9b8d36e25ba7349ed63d9b64010c04aa27b7e09c2
- Size of remote file:
- 3.06 GB
- SHA256:
- 32d63207e8c743d2da2900442f8bf94fd8c8a85a3119075240c9586f909c266e
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