Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Malayalam
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use simpragma/breeze-dsw-base-ml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simpragma/breeze-dsw-base-ml with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="simpragma/breeze-dsw-base-ml")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("simpragma/breeze-dsw-base-ml") model = AutoModelForSpeechSeq2Seq.from_pretrained("simpragma/breeze-dsw-base-ml", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d1d73f23ca48cb0623a0ec540833d6ba54082da1016febb5ed7199d9c58d264
- Size of remote file:
- 198 MB
- SHA256:
- 6838bb689c85551eeda3dca49dad6c71c88a49882b477c9c2da05aa1bff9d91e
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