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Browse files- README.md +42 -0
- adapter_config.json +40 -0
- head_config.json +25 -0
- pytorch_adapter.bin +3 -0
- pytorch_model_head.bin +3 -0
README.md
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---
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tags:
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- adapter-transformers
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- roberta
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datasets:
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- BigTMiami/citation_intent_dataset
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---
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# Adapter `BigTMiami/m_cite_par_bn_v_4_class_no_pre_1_adapter` for roberta-base
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An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/citation_intent_dataset](https://huggingface.co/datasets/BigTMiami/citation_intent_dataset/) dataset and includes a prediction head for classification.
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This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library.
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## Usage
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First, install `adapters`:
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```
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pip install -U adapters
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```
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Now, the adapter can be loaded and activated like this:
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```python
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from adapters import AutoAdapterModel
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model = AutoAdapterModel.from_pretrained("roberta-base")
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adapter_name = model.load_adapter("BigTMiami/m_cite_par_bn_v_4_class_no_pre_1_adapter", source="hf", set_active=True)
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```
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## Architecture & Training
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<!-- Add some description here -->
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## Evaluation results
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<!-- Add some description here -->
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## Citation
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<!-- Add some description here -->
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adapter_config.json
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{
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"config": {
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"adapter_residual_before_ln": false,
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"cross_adapter": false,
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"factorized_phm_W": true,
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"factorized_phm_rule": false,
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"hypercomplex_nonlinearity": "glorot-uniform",
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"init_weights": "mam_adapter",
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"inv_adapter": null,
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"inv_adapter_reduction_factor": null,
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"is_parallel": true,
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"learn_phm": true,
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"leave_out": [],
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"ln_after": false,
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"ln_before": false,
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"mh_adapter": false,
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"non_linearity": "relu",
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"original_ln_after": true,
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"original_ln_before": false,
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"output_adapter": true,
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"phm_bias": true,
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"phm_c_init": "normal",
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"phm_dim": 4,
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"phm_init_range": 0.0001,
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"phm_layer": false,
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"phm_rank": 1,
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"reduction_factor": 16,
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"residual_before_ln": true,
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"scaling": 4.0,
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"shared_W_phm": false,
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"shared_phm_rule": true,
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"use_gating": false
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},
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"hidden_size": 768,
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"model_class": "RobertaAdapterModel",
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"model_name": "roberta-base",
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"model_type": "roberta",
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"name": "m_cite_par_bn_v_4_class_no_pre_1",
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"version": "0.1.2"
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}
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head_config.json
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{
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"config": {
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"activation_function": "tanh",
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"bias": true,
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"dropout_prob": null,
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"head_type": "classification",
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"label2id": {
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"Background": 0,
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"CompareOrContrast": 2,
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"Extends": 3,
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"Future": 5,
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"Motivation": 4,
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"Uses": 1
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},
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"layers": 2,
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"num_labels": 6,
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"use_pooler": false
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},
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"hidden_size": 768,
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"model_class": "RobertaAdapterModel",
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"model_name": "roberta-base",
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"model_type": "roberta",
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"name": "m_cite_par_bn_v_4_class_no_pre_1",
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"version": "0.1.2"
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}
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pytorch_adapter.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:865a20bc97e18eb7209232f42300f9902006c770cfc6ba42ceea7532fa31fd64
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size 3596902
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pytorch_model_head.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:561e9fe1c7c5e2166239fbd09038a41e7883b93ff1eaeb40c15cf4109ff795d9
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size 2383080
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