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:
- 6604900b8fd5c001d3037bd5e271a4ce0fbd530b702d1202d5405574471d3bc1
- Size of remote file:
- 3.06 GB
- SHA256:
- 566e1f44b4698a2e6ec7448c12fb303388a2082194d829534300aee108a15b81
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