Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Marathi
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use shripadbhat/whisper-medium-mr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shripadbhat/whisper-medium-mr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shripadbhat/whisper-medium-mr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shripadbhat/whisper-medium-mr") model = AutoModelForSpeechSeq2Seq.from_pretrained("shripadbhat/whisper-medium-mr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1d31adfc99c7d1f2593e4245362bde0777a99d52180fc3d8297a02d39f6c52c
- Size of remote file:
- 3.06 GB
- SHA256:
- b35eaf02f912bdd56dce53b458c70d9d720702c81bc0886f5b44d96826a2e5cc
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