Added README file and removed (bad) TF file

README.md

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+---
+language: 
+- multilingual
+- pt
+- en
+tags:
+- xlm-roberta-large
+- semantic role labeling
+- finetuned
+license: Apache 2.0
+datasets:
+- PropBank.Br
+- CoNLL-2012
+metrics:
+- F1 Measure
+---
+
+# MyModel
+
+## Model description
+
+This model is the [`xlm-roberta-large`](https://huggingface.co/xlm-roberta-large) fine-tuned on the English CoNLL formatted OntoNotes v5.0 semantic role labeling data. This is part of a project from which resulted the following models:
+
+* [liaad/srl-pt_bertimbau-base](https://huggingface.co/liaad/srl-pt_bertimbau-base)
+* [liaad/srl-pt_bertimbau-large](https://huggingface.co/liaad/srl-pt_bertimbau-large)
+* [liaad/srl-pt_xlmr-base](https://huggingface.co/liaad/srl-pt_xlmr-base)
+* [liaad/srl-pt_xlmr-large](https://huggingface.co/liaad/srl-pt_xlmr-large)
+* [liaad/srl-pt_mbert-base](https://huggingface.co/liaad/srl-pt_mbert-base)
+* [liaad/srl-en_xlmr-base](https://huggingface.co/liaad/srl-en_xlmr-base)
+* [liaad/srl-en_xlmr-large](https://huggingface.co/liaad/srl-en_xlmr-large)
+* [liaad/srl-en_mbert-base](https://huggingface.co/liaad/srl-en_mbert-base)
+* [liaad/srl-enpt_xlmr-base](https://huggingface.co/liaad/srl-enpt_xlmr-base)
+* [liaad/srl-enpt_xlmr-large](https://huggingface.co/liaad/srl-enpt_xlmr-large)
+* [liaad/srl-enpt_mbert-base](https://huggingface.co/liaad/srl-enpt_mbert-base)
+* [liaad/ud_srl-pt_bertimbau-large](https://huggingface.co/liaad/ud_srl-pt_bertimbau-large)
+* [liaad/ud_srl-pt_xlmr-large](https://huggingface.co/liaad/ud_srl-pt_xlmr-large)
+* [liaad/ud_srl-enpt_xlmr-large](https://huggingface.co/liaad/ud_srl-enpt_xlmr-large)
+
+For more information, please see the accompanying article (See BibTeX entry and citation info below) and the [project's github](https://github.com/asofiaoliveira/srl_bert_pt).
+
+
+## Intended uses & limitations
+
+#### How to use
+
+To use the transformers portion of this model:
+```python
+from transformers import AutoTokenizer, AutoModel
+
+tokenizer = AutoTokenizer.from_pretrained("liaad/srl-en_xlmr-large")
+model = AutoModel.from_pretrained("liaad/srl-en_xlmr-large")
+```
+
+To use the full SRL model (transformers portion + a decoding layer), refer to the [project's github](https://github.com/asofiaoliveira/srl_bert_pt).
+
+
+#### Limitations and bias
+
+- This model does not include a Tensorflow version. This is because the "type_vocab_size" in this model was changed (from 1 to 2) and, therefore, it cannot be easily converted to Tensorflow.
+- The models were trained only for 5 epochs.
+- The English data was preprocessed to match the Portuguese data, so there are some differences in role attributions and some roles were removed from the data.
+
+
+## Training data
+
+Pretrained weights were left identical to the original model [`xlm-roberta-large`](https://huggingface.co/xlm-roberta-large). A randomly initialized embeddings layer for "token_type_ids" was added.
+
+
+## Training procedure
+
+The models were trained on the CoNLL-2012 dataset, preprocessed to match the Portuguese PropBank.Br data, using Cross-Validation. They were tested on the folds as well as on a smaller opinion dataset "Buscapé". For more information, please see the accompanying article (See BibTeX entry and citation info below) and the [project's github](https://github.com/asofiaoliveira/srl_bert_pt).
+
+## Eval results
+
+
+| Model Name | F<sub>1</sub> CV PropBank.Br (in domain) | F<sub>1</sub> Buscapé (out of domain) |
+| --------------- | ------ | ----- | 
+| `srl-pt_bertimbau-base` | 76.30 | 73.33 | 
+| `srl-pt_bertimbau-large` | 77.42 | 74.85 | 
+| `srl-pt_xlmr-base` | 75.22 | 72.82 | 
+| `srl-pt_xlmr-large` | 77.59 | 73.84 | 
+| `srl-pt_mbert-base` | 72.76 | 66.89 | 
+| `srl-en_xlmr-base` | 66.59 | 65.24 | 
+| `srl-en_xlmr-large` | 67.60 | 64.94 | 
+| `srl-en_mbert-base` | 63.07 | 58.56 | 
+| `srl-enpt_xlmr-base` | 76.50 | 73.74 | 
+| `srl-enpt_xlmr-large` | **78.22** | 74.55 | 
+| `srl-enpt_mbert-base` | 74.88 | 69.19 | 
+| `ud_srl-pt_bertimbau-large` | 77.53 | 74.49 | 
+| `ud_srl-pt_xlmr-large` | 77.69 | 74.91 |
+| `ud_srl-enpt_xlmr-large` | 77.97 | **75.05** | 
+
+
+### BibTeX entry and citation info
+
+```bibtex
+@misc{oliveira2021transformers,
+      title={Transformers and Transfer Learning for Improving Portuguese Semantic Role Labeling}, 
+      author={Sofia Oliveira and Daniel Loureiro and Alípio Jorge},
+      year={2021},
+      eprint={2101.01213},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```

tf_model.h5

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