Automatic Speech Recognition
Transformers
PyTorch
JAX
Kannada
whisper
whisper-event
Eval Results (legacy)
Instructions to use vasista22/whisper-kannada-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vasista22/whisper-kannada-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vasista22/whisper-kannada-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vasista22/whisper-kannada-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("vasista22/whisper-kannada-tiny") - Notebooks
- Google Colab
- Kaggle
Upload FlaxWhisperForConditionalGeneration
#3 opened over 1 year ago
by
yndeepak
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#1 opened over 2 years ago
by
SFconvertbot