Introduction of ovos-model2vec-intents-potion-retrieval-32M
Model Details of ovos-model2vec-intents-potion-retrieval-32M
m2v_intents_potion-retrieval-32M 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("m2v_intents_potion-retrieval-32M")
# Predict labels
predicted = model.predict(["Example sentence"])
@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}
}
Runs of Jarbas ovos-model2vec-intents-potion-retrieval-32M on huggingface.co
8
Total runs
0
24-hour runs
-8
3-day runs
-9
7-day runs
2
30-day runs
More Information About ovos-model2vec-intents-potion-retrieval-32M huggingface.co Model
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ovos-model2vec-intents-potion-retrieval-32M is an open source model from GitHub that offers a free installation service, and any user can find ovos-model2vec-intents-potion-retrieval-32M on GitHub to install. At the same time, huggingface.co provides the effect of ovos-model2vec-intents-potion-retrieval-32M install, users can directly use ovos-model2vec-intents-potion-retrieval-32M installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
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