Instructions to use vivekharry/tripura-st-lab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vivekharry/tripura-st-lab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vivekharry/tripura-st-lab")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vivekharry/tripura-st-lab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Tripura ST Lab
Training code and dataset registry for Kokborok-first speech translation, then Bengali and Marathi on BhasaAnuvaad.
Landing page: https://huggingface.co/spaces/vivekharry/tripura-st-lab-site
Kokborok AUDIO (16 kHz mono)
โ ASR (MMS-1B + NE-ASR adapter, or Whisper fine-tune)
Kokborok transcript
โ MT (NLLB / sdmy/kokborok)
English
Clone this repo, then:
pip install -e .
python -m indic_st.train_asr --dataset kokborok_asr --init-from openai/whisper-small
python -m indic_st.train_mt --dataset kokborok_mt
See the full README in the files tab for dataset IDs, tonal-augmentation rules, and citations.
Author: Vivek Das (vivekharry).