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---
tags:
- adapterhub:nli/qnli
- text-classification
- adapter-transformers
- distilbert
license: "apache-2.0"
---
# Adapter `distilbert-base-uncased_nli_qnli_pfeiffer` for distilbert-base-uncased
Adapter for distilbert-base-uncased in Pfeiffer architecture trained on the QNLI dataset for 15 epochs with early stopping and a learning rate of 1e-4.
**This adapter was created for usage with the [Adapters](https://github.com/Adapter-Hub/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("distilbert-base-uncased")
adapter_name = model.load_adapter("AdapterHub/distilbert-base-uncased_nli_qnli_pfeiffer")
model.set_active_adapters(adapter_name)
```
## Architecture & Training
- Adapter architecture: pfeiffer
- Prediction head: classification
- Dataset: [QNLI](https://adapterhub.ml/explore/nli/qnli/)
## Author Information
- Author name(s): Clifton Poth
- Author email: [email protected]
- Author links: [Website](https://calpt.github.io), [GitHub](https://github.com/calpt), [Twitter](https://twitter.com/@clifapt)
## Citation
```bibtex
```
*This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/distilbert-base-uncased_nli_qnli_pfeiffer.yaml*. |