Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Czech
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use sgangireddy/whisper-base-cv-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgangireddy/whisper-base-cv-cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sgangireddy/whisper-base-cv-cs")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sgangireddy/whisper-base-cv-cs") model = AutoModelForSpeechSeq2Seq.from_pretrained("sgangireddy/whisper-base-cv-cs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b95c2a64932078e8ade61dbffee9afb5684a8a52e23ea4e899c2a7350e5bce5
- Size of remote file:
- 290 MB
- SHA256:
- 748fe2667d955d8d62619ccb53f4ae818a350c223bd27466ee32e71e0f5f5a71
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