Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Bengali
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use mkbackup/testing_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkbackup/testing_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mkbackup/testing_model")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mkbackup/testing_model") model = AutoModelForSpeechSeq2Seq.from_pretrained("mkbackup/testing_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e78b043b7502116a13fc0be3bba3850fd79f128ea72b0b640d569e95c9391f08
- Size of remote file:
- 967 MB
- SHA256:
- 03a20545e04d9958980bef56292327569585462def6b6f1dfc562eb7c7b0e52c
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