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AdapterHub/facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer
facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer is a machine learning model from AdapterHub. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for adapter-transformers. The card lists the license as apache-2.0.
Adapter for mbart-large-cc25 in Pfeiffer architecture with reduction factor 2 trained on the WMT16 Romanian-English translation task. Training for 10 epochs with early stopping and a learning rate of 1e-4. After post-…
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From the Hugging Face model README
facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer for facebook/mbart-large-cc25Adapter for mbart-large-cc25 in Pfeiffer architecture with reduction factor 2 trained on the WMT16 Romanian-English translation task. Training for 10 epochs with early stopping and a learning rate of 1e-4. After post-processing following https://github.com/huggingface/transformers/blob/master/examples/legacy/seq2seq/romanian_postprocessing.md, it achieves a BLEU score of 36.3.
This adapter was created for usage with the Adapters library.
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/mbart-large-cc25")
adapter_name = model.load_adapter("AdapterHub/facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer")
model.set_active_adapters(adapter_name)
This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer.yaml.