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:
- f77f88db027888fac8657fc943ff7e970e389d9c89b33718df60fc51efb98ce5
- Size of remote file:
- 3.64 kB
- SHA256:
- d1e7f78949b73a0c59cd5c043ed077708a5bfaeae7fbbfa4f349c77cfe588581
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