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Adapter facebook-bart-large_qa_squad2_lohfink-rossi-leaveout for facebook/bart-large

Note: This adapter was not trained by the AdapterHub team, but by these author(s): Till Lohfink & Maria Rossi (Contributed equally.). See author details below.

Adapter for bart-large using a custom architecture (Lohfink-Rossi-Leaveout) trained on the SQuAD 2.0 dataset for 15 epochs with a Cosine with Restarts learning rate scheduler ans learning rate 0.001.

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("facebook/bart-large")
adapter_name = model.load_adapter("AdapterHub/facebook-bart-large_qa_squad2_lohfink-rossi-leaveout")
model.set_active_adapters(adapter_name)

Architecture & Training

  • Adapter architecture: lohfink-rossi-leaveout
  • Prediction head: question answering
  • Dataset: SQuAD 2.0

Author Information

Citation


This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/lohfink-rossi/facebook-bart-large_qa_squad2_lohfink-rossi-leaveout.yaml.

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Inference API
This model can be loaded on Inference API (serverless).

Dataset used to train AdapterHub/facebook-bart-large_qa_squad2_lohfink-rossi-leaveout