| --- |
| library_name: model2vec |
| license: mit |
| model_name: cnmoro/custom-model2vec-tokenlearn-medium |
| tags: |
| - embeddings |
| - static-embeddings |
| - sentence-transformers |
| language: |
| - pt |
| - en |
| --- |
| A custom model2vec model, trained using a modified version of the [tokenlearn](https://github.com/MinishLab/tokenlearn) library. |
|
|
| Base model is nomic-ai/nomic-embed-text-v2-moe. |
|
|
| The output dimension is 256, and the vocabulary size is 249.999 |
|
|
| The training process used a mix of English (10%) and Portuguese (90%) texts. |
|
|
| ```python |
| from model2vec import StaticModel |
| |
| # Load a pretrained Sentence Transformer model |
| model = StaticModel.from_pretrained("cnmoro/custom-model2vec-tokenlearn-medium") |
| |
| # Compute text embeddings |
| embeddings = model.encode(["Example sentence"]) |
| ``` |
