| tags: | |
| - bert | |
| - adapter-transformers | |
| - adapterhub:pico_ner | |
| datasets: | |
| - reginaboateng/cleaned_ebmnlp_pico | |
| # Adapter `reginaboateng/BERT_adapter_ner_pico_for_classification_task` for bert-base-uncased | |
| An [adapter](https://adapterhub.ml) for the `bert-base-uncased` model that was trained on the [pico_ner](https://adapterhub.ml/explore/pico_ner/) dataset. | |
| This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library. | |
| ## Usage | |
| First, install `adapter-transformers`: | |
| ``` | |
| pip install -U adapter-transformers | |
| ``` | |
| _Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. [More](https://docs.adapterhub.ml/installation.html)_ | |
| Now, the adapter can be loaded and activated like this: | |
| ```python | |
| from transformers import AutoAdapterModel | |
| model = AutoAdapterModel.from_pretrained("bert-base-uncased") | |
| adapter_name = model.load_adapter("reginaboateng/BERT_adapter_ner_pico_for_classification_task", source="hf", set_active=True) | |
| ``` | |
| ## Architecture & Training | |
| <!-- Add some description here --> | |
| ## Evaluation results | |
| <!-- Add some description here --> | |
| ## Citation | |
| <!-- Add some description here --> |