Instructions to use StephennFernandes/wav2vec2-XLS-R-300m-konkani with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StephennFernandes/wav2vec2-XLS-R-300m-konkani with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="StephennFernandes/wav2vec2-XLS-R-300m-konkani")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("StephennFernandes/wav2vec2-XLS-R-300m-konkani") model = AutoModelForCTC.from_pretrained("StephennFernandes/wav2vec2-XLS-R-300m-konkani") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 30.0, | |
| "eval_loss": 0.5320505499839783, | |
| "eval_runtime": 210.2131, | |
| "eval_samples": 3401, | |
| "eval_samples_per_second": 16.179, | |
| "eval_steps_per_second": 1.013, | |
| "eval_wer": 0.3199213685223138, | |
| "train_loss": 0.5493880579162342, | |
| "train_runtime": 54395.2991, | |
| "train_samples": 30605, | |
| "train_samples_per_second": 16.879, | |
| "train_steps_per_second": 0.264 | |
| } |