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Jarbas/ovos-model2vec-intents-potion-2M
ovos-model2vec-intents-potion-2M is a machine learning model from Jarbas. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for model2vec. The card lists the license as mit.
Deprecated. This model is superseded and is kept only so existing installs keep resolving. It was trained before the OVOS intent corpus was rebuilt from a pinned, reproducible pipeline, and its label set no longer mat…
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From the Hugging Face model README
Deprecated. This model is superseded and is kept only so existing installs keep resolving. It was trained before the OVOS intent corpus was rebuilt from a pinned, reproducible pipeline, and its label set no longer matches what the OVOS m2v pipeline registers.
Use OpenVoiceOS/ovos-m2v-intents-multilingual instead, or OpenVoiceOS/ovos-m2v-intents-en on an English-only device. Both ship a
labels.jsonbeside the weights.
This Model2Vec model is a fine-tuned version of the potion-base-2M Model2Vec model. It also includes a classifier head on top.
Install model2vec using pip:
pip install model2vec[inference]
Load this model using the from_pretrained method:
from model2vec.inference import StaticModelPipeline
# Load a pretrained Model2Vec model
model = StaticModelPipeline.from_pretrained("model_en_potion-base-2M")
# Predict labels
predicted = model.predict(["Example sentence"])
Model2Vec was developed by the Minish Lab team consisting of Stephan Tulkens and Thomas van Dongen.
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}
}