Feature Extraction
Model2Vec
Safetensors
English
Portuguese

This Model2Vec model was created by using Tokenlearn, with nomic-embed-text-v2-moe as a base, trained on around 20M passages (english and portuguese).

The output dimension is 50.

This is supposed to be a more minimalistic version of cnmoro/static-nomic-eng-ptbr

Usage

Load this model using the from_pretrained method:

from model2vec import StaticModel

# Load a pretrained Model2Vec model
model = StaticModel.from_pretrained("cnmoro/static-nomic-eng-ptbr-tiny")

# Compute text embeddings
embeddings = model.encode(["Example sentence"])
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Model size
12.5M params
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F32
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