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
| { | |
| "epoch": 29.02, | |
| "eval_loss": 0.6259765625, | |
| "eval_runtime": 1588.1017, | |
| "eval_samples_per_second": 0.417, | |
| "eval_steps_per_second": 0.026, | |
| "eval_wer": 42.72474513438369 | |
| } |