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
File size: 401 Bytes
3b18175 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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
} |