Upload MBartForConditionalGeneration
Browse files- README.md +43 -0
- adapter_config.json +40 -0
- head_config.json +15 -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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- adapterhub:summarization/dinamina_5400_full_text
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- mbart
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- adapter-transformers
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datasets:
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- dinamina_5400_full_text
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---
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# Adapter `Pubudu/mbart-large-50_scaled_par_bn_rf_16_dinamina_5400` for facebook/mbart-large-50
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An [adapter](https://adapterhub.ml) for the `facebook/mbart-large-50` model that was trained on the [summarization/dinamina_5400_full_text](https://adapterhub.ml/explore/summarization/dinamina_5400_full_text/) dataset.
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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("facebook/mbart-large-50")
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adapter_name = model.load_adapter("Pubudu/mbart-large-50_scaled_par_bn_rf_16_dinamina_5400", 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": 2,
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"residual_before_ln": true,
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"scaling": "learned",
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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": 1024,
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"model_class": "MBartForConditionalGeneration",
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"model_name": "facebook/mbart-large-50",
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"model_type": "mbart",
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"name": "mbart-large-50_scaled_par_bn_rf_16_dinamina_5400",
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"version": "0.1.1"
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}
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head_config.json
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{
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"config": null,
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"hidden_size": 1024,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"model_class": "MBartForConditionalGeneration",
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"model_name": "facebook/mbart-large-50",
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"model_type": "mbart",
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"name": null,
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"num_labels": 3,
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"version": "0.1.1"
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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:ddafa853cdc057a7f33558db6851d708f9152b6d6e33a960e64d70c4002cad2f
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size 100860194
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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:adcc43a196d39e07adb0d2ce5a89621565caf0187b28c81222c9bb08b8fa37f7
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size 1025227034
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