Instructions to use mikav-ai/mikav with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikav-ai/mikav with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mikav-ai/mikav", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Data | |
| Place datasets here by processing stage. | |
| - `raw/`: original downloaded or manually collected data. | |
| - `cleaned/`: normalized Malayalam text. | |
| - `deduplicated/`: cleaned text after exact and fuzzy deduplication. | |
| - `tokenized/`: model-ready tokenized datasets. | |
| Do not commit large datasets directly unless they are intentionally small samples. | |