selimyagci
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Browse files- README.md +40 -0
- adapter_config.json +41 -0
- head_config.json +18 -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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- t5
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---
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# Adapter `selimyagci/f_qa_t5` for google-t5/t5-small
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An [adapter](https://adapterhub.ml) for the `google-t5/t5-small` model that was trained on the None dataset and includes a prediction head for seq2seq lm.
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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("google-t5/t5-small")
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adapter_name = model.load_adapter("selimyagci/f_qa_t5", 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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"dropout": 0.0,
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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": "bert",
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"inv_adapter": null,
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"inv_adapter_reduction_factor": null,
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"is_parallel": false,
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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": true,
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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": 1.0,
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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": 512,
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"model_class": "T5AdapterModel",
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"model_name": "google-t5/t5-small",
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"model_type": "t5",
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"name": "f_qa",
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"version": "adapters.1.0.0"
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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": null,
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"bias": false,
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"head_type": "seq2seq_lm",
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"label2id": null,
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"layer_norm": false,
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"layers": 1,
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"shift_labels": false,
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"vocab_size": 32128
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},
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"hidden_size": 512,
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"model_class": "T5AdapterModel",
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"model_name": "google-t5/t5-small",
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"model_type": "t5",
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"name": "f_qa",
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"version": "adapters.1.0.0"
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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 sha256:37ef720ea15cbdea740b3623e009914da2b82f2ede7668f13f71c7f5759dc393
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size 1616614
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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 sha256:150da81e7c67424637501057015c07b6a731db26f6321b5fde8b0e7e2b7fadf4
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size 65799443
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