Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
whisper-event
Eval Results (legacy)
Instructions to use sgangireddy/whisper-medium-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgangireddy/whisper-medium-cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sgangireddy/whisper-medium-cs")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sgangireddy/whisper-medium-cs") model = AutoModelForSpeechSeq2Seq.from_pretrained("sgangireddy/whisper-medium-cs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d36ac80d8621f8d53c0e6534244185edd03c609b07ac45eca58c0b11c1f6ecf3
- Size of remote file:
- 3.52 kB
- SHA256:
- fcbb830b872163a85d2d75fcd3f4d6109e07dd16b61dd3d1e752861b270871a1
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