Adapter distilbert-base-uncased_comsense_hellaswag_pfeiffer
for distilbert-base-uncased
Adapter for distilbert-base-uncased in Pfeiffer architecture trained on the Hellaswag dataset for 15 epochs with early stopping and a learning rate of 1e-4.
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:
from adapters import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("distilbert-base-uncased")
adapter_name = model.load_adapter("AdapterHub/distilbert-base-uncased_comsense_hellaswag_pfeiffer")
model.set_active_adapters(adapter_name)
Architecture & Training
- Adapter architecture: pfeiffer
- Prediction head: multiple choice
- Dataset: HellaSwag
Author Information
- Author name(s): Clifton Poth
- Author email: [email protected]
- Author links: Website, GitHub, Twitter
Citation
This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/distilbert-base-uncased_comsense_hellaswag_pfeiffer.yaml.
- Downloads last month
- 0
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The HF Inference API does not support multiple-choice models for adapter-transformers library.