metadata
library_name: model2vec
license: mit
model_name: cnmoro/custom-model2vec-tokenlearn-small
tags:
- embeddings
- static-embeddings
- sentence-transformers
language:
- pt
- en
A custom model2vec model, trained using a modified version of the tokenlearn library.
Base model is nomic-ai/nomic-embed-text-v2-moe.
The output dimension is 256, and the vocabulary size is 10.000.
The training process used a mix of English (10%) and Portuguese (90%) texts.
from model2vec import StaticModel
# Load a pretrained Sentence Transformer model
model = StaticModel.from_pretrained("cnmoro/custom-model2vec-tokenlearn-small")
# Compute text embeddings
embeddings = model.encode(["Example sentence"])