Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Giryama
whisper
Generated from Trainer
Instructions to use kazeric/whisper_small_no_overfit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kazeric/whisper_small_no_overfit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kazeric/whisper_small_no_overfit")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kazeric/whisper_small_no_overfit") model = AutoModelForSpeechSeq2Seq.from_pretrained("kazeric/whisper_small_no_overfit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c203f07da71e44700a35253052afb774ff80adf57b2cc87b86be924cf3a38ce6
- Size of remote file:
- 5.56 kB
- SHA256:
- b42e9b4a28d6624a23f72fa15127d65fb9a71fd572e50603881e43119d8b04bd
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