Instructions to use desert-ant-labs/emo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use desert-ant-labs/emo with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| # Third-party notices โ emo | |
| The `emo` model derives from components licensed by third parties. Their licenses | |
| apply to the components named below; nothing in the Desert Ant Labs | |
| Source-Available License overrides them. | |
| ## Semantic embedding | |
| ### potion-multilingual-128M โ MinishLab | |
| - **Source:** [`minishlab/potion-multilingual-128M`](https://huggingface.co/minishlab/potion-multilingual-128M) | |
| - **License:** MIT | |
| - **Use in `emo`:** the semantic stream. The shipped semantic table is a | |
| PCA-reduced (112-dim) and vocab-pruned (~45k token) derivative of this model's | |
| embeddings. Its SentencePiece tokenizer (XLM-RoBERTa lineage) is used at | |
| inference to tokenize text for that stream. | |
| ### bge-m3 โ BAAI | |
| - **Source:** [`BAAI/bge-m3`](https://huggingface.co/BAAI/bge-m3) | |
| - **License:** MIT | |
| - **Use in `emo`:** teacher model. `potion-multilingual-128M` was distilled from | |
| `bge-m3` (via Model2Vec / Tokenlearn), so `emo`'s semantic stream derives from it. | |
| ### Model2Vec / Tokenlearn โ MinishLab | |
| - **Source:** [github.com/MinishLab/model2vec](https://github.com/MinishLab/model2vec) | |
| - **License:** MIT | |
| - **Use in `emo`:** the static-embedding distillation method behind the semantic stream. | |
| ## Training data | |
| ### Unicode CLDR โ Unicode, Inc. | |
| - **Source:** [cldr.unicode.org](https://cldr.unicode.org) (emoji annotations / keywords). | |
| - **License:** Unicode License Agreement โ Data Files and Software (UNICODE-DFS-2016). | |
| - **Use in `emo`:** multilingual emoji keywords were used as grounding examples when | |
| building the training data. CLDR data is not redistributed in this repository. | |