Jarbas / ovos-model2vec-intents-roberta-large-bne

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Total runs: 11
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7-day runs: 1
30-day runs: 6
Model's Last Updated: September 02 2026

Introduction of ovos-model2vec-intents-roberta-large-bne

Model Details of ovos-model2vec-intents-roberta-large-bne

ovos-intents-es-b32e30-n1d128-m2v-256-roberta-large-bne Model Card

This Model2Vec model is a fine-tuned version of the unknown Model2Vec model. It also includes a classifier head on top.

Installation

Install model2vec using pip:

pip install model2vec[inference]
Usage

Load this model using the from_pretrained method:

from model2vec.inference import StaticModelPipeline

# Load a pretrained Model2Vec model
model = StaticModelPipeline.from_pretrained("ovos-intents-es-b32e30-n1d128-m2v-256-roberta-large-bne")

# Predict labels
predicted = model.predict(["Example sentence"])
Additional Resources
Library Authors

Model2Vec was developed by the Minish Lab team consisting of Stephan Tulkens and Thomas van Dongen .

Citation

Please cite the Model2Vec repository if you use this model in your work.

@article{minishlab2024model2vec,
  author = {Tulkens, Stephan and {van Dongen}, Thomas},
  title = {Model2Vec: Fast State-of-the-Art Static Embeddings},
  year = {2024},
  url = {https://github.com/MinishLab/model2vec}
}

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11
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0
3-day runs
1
7-day runs
6
30-day runs

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