Instructions to use Splend1dchan/wav2vecu2-t5lephone-small-NMSQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Splend1dchan/wav2vecu2-t5lephone-small-NMSQA with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Splend1dchan/wav2vecu2-t5lephone-small-NMSQA") model = AutoModelForMultimodalLM.from_pretrained("Splend1dchan/wav2vecu2-t5lephone-small-NMSQA") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
wav2vecu2 -> phoneme from answer timespan, get answer phoneme train NMSQA tasks with context phoneme as input and answer phoneme as output
Results Avg AOS: 0.6586811819639634 Avg FF1: 0.697483897268189 Exact Match: 0.2042313923568093
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