Beta

Explore
Marketplace
Neural Labs
Chat
Wallet
Docs

Beta

Explore Marketplace Neural Labs Wallet Docs

Build

Manage

My assets Manage wallet Organization

Community

Discord X (Twitter)Telegram

Docs Privacy Policy Terms and Conditions

Proud member of

Proud member of

Docs Cookie Policy

Privacy Policy Terms and Conditions

© 2026 AlphaNeural AI. All rights reserved.

roberta-large-cola_pfeiffer – AI Model by AdapterHub | AlphaNeural AI

You can deploy this model and start earning money today!

AdapterHub/
roberta-large-cola_pfeiffer

like

0

adapter-transformers

text-classification

lingaccept/cola

Views

No views yet

Adapter `roberta-large-cola_pfeiffer` for roberta-large

Adapter (with head) trained using the run_glue.py script with an extension that retains the best checkpoint (out of 30 epochs).

This adapter was created for usage with the Adapters library.

Usage

First, install adapters:

pip install -U adapters

Now, the adapter can be loaded and activated like this:

python

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("roberta-large")
adapter_name = model.load_adapter("AdapterHub/roberta-large-cola_pfeiffer")
model.set_active_adapters(adapter_name)

Architecture & Training

Adapter architecture: pfeiffer
Prediction head: classification
Dataset: CoLA

Author Information

Author name(s): Andreas Rücklé
Author email: rueckle@ukp.informatik.tu-darmstadt.de
Author links: Website, GitHub, Twitter

Citation

bibtex

@article{pfeiffer2020AdapterHub,
    title={AdapterHub: A Framework for Adapting Transformers},
    author={Jonas Pfeiffer,
            Andreas R\"uckl\'{e},
            Clifton Poth,
            Aishwarya Kamath,
            Ivan Vuli\'{c},
            Sebastian Ruder,
            Kyunghyun Cho,
            Iryna Gurevych},
    journal={ArXiv},
    year={2020}
}

This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/roberta-large-cola_pfeiffer.yaml.