calpt's picture
Add inference API tag & update citation
- token-classification
- roberta
- adapterhub:ner/mit_movie_trivia
- adapter-transformers
- en
# Adapter `AdapterHub/roberta-base-pf-mit_movie_trivia` for roberta-base
An [adapter]( for the `roberta-base` model that was trained on the [ner/mit_movie_trivia]( dataset and includes a prediction head for tagging.
This adapter was created for usage with the **[adapter-transformers](** library.
## Usage
First, install `adapter-transformers`:
pip install -U adapter-transformers
_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. [More](
Now, the adapter can be loaded and activated like this:
from transformers import AutoModelWithHeads
model = AutoModelWithHeads.from_pretrained("roberta-base")
adapter_name = model.load_adapter("AdapterHub/roberta-base-pf-mit_movie_trivia", source="hf")
model.active_adapters = adapter_name
## Architecture & Training
The training code for this adapter is available at
In particular, training configurations for all tasks can be found [here](
## Evaluation results
Refer to [the paper]( for more information on results.
## Citation
If you use this adapter, please cite our paper ["What to Pre-Train on? Efficient Intermediate Task Selection"](
title = "{W}hat to Pre-Train on? {E}fficient Intermediate Task Selection",
author = {Poth, Clifton and
Pfeiffer, Jonas and
R{"u}ckl{'e}, Andreas and
Gurevych, Iryna},
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "",
pages = "10585--10605",