Downloads · 30 days
6
15% of all-time downloads
model2vec-ATC-role-classification-potion-32M
TigreGotico/model2vec-ATC-role-classification-potion-32M
model2vec-ATC-role-classification-potion-32M is a machine learning model from TigreGotico. 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.
This Model2Vec model is a fine-tuned version of the unknown Model2Vec model. It also includes a classifier head on top.
All-time downloads
41
Public
Parameters
32.4M
137 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors130 MB · 94%
Parameter types
How the weights are stored.
F3232.4M · 100%
Base models
Model card
From the Hugging Face model README
atc-pilot-speaker-role-potion-base-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("atc-pilot-speaker-role-potion-base-32M")
# 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}
}
- Library
- model2vec
- License
- mit
- Languages
- en
- Created
- Feb 14, 2026
- Updated
- Feb 14, 2026