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---
tags:
- gpt2
- adapterhub:nli/rte
- adapter-transformers
- text-classification
license: "apache-2.0"
---
# Adapter `gpt2_nli_rte_houlsby` for gpt2
Adapter for gpt2 in Houlsby architecture trained on the RTE dataset for 10 epochs with 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("gpt2")
adapter_name = model.load_adapter("AdapterHub/gpt2_nli_rte_houlsby")
model.set_active_adapters(adapter_name)
```
## Architecture & Training
- Adapter architecture: houlsby
- Prediction head: classification
- Dataset: [RTE](https://aclweb.org/aclwiki/Recognizing_Textual_Entailment)
## Author Information
- Author name(s): Hannah Sterz
- Author email: [email protected]
- Author links: [Twitter](https://twitter.com/@h_sterz)
## Citation
```bibtex
```
*This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/gpt2_nli_rte_houlsby.yaml*. |