Instructions to use StephennFernandes/wav2vec2-XLS-R-300m-assamese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StephennFernandes/wav2vec2-XLS-R-300m-assamese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="StephennFernandes/wav2vec2-XLS-R-300m-assamese")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("StephennFernandes/wav2vec2-XLS-R-300m-assamese") model = AutoModel.from_pretrained("StephennFernandes/wav2vec2-XLS-R-300m-assamese") - Notebooks
- Google Colab
- Kaggle
Commit History
upload train_result.json 5f7c476
Upload preprocessor_config.json 29d5939
add tokenizer b77c3b2
add model 5914caf
StephennFernandes commited on