Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Czech
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use maag/whisper_tiny_cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maag/whisper_tiny_cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="maag/whisper_tiny_cs")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("maag/whisper_tiny_cs") model = AutoModelForSpeechSeq2Seq.from_pretrained("maag/whisper_tiny_cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 380ce20c1f1b4a98f83043f90a8031516a327cb4cdc21fe347d1756ee4d52019
- Size of remote file:
- 231 MB
- SHA256:
- 1dc96807cbbecdd4a1c27b04cd6abd850841bb6ceeb347ebeb2c09d02ba2ef27
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