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README.md

@@ -5,7 +5,6 @@ datasets:
 - assin2
 ---
 
-
 # BERTimbau large for Recognizing Textual Entailment
 
 This is the [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) model finetuned for 
@@ -13,7 +12,7 @@ Recognizing Textual Entailment with the [ASSIN 2](https://huggingface.co/dataset
 This model is suitable for Portuguese.
 
 - Git Repo: [Evaluation of Portuguese Language Models](https://github.com/ruanchaves/eplm).
-- Demo: [Hugging Face Space: Portuguese Text Simplification](https://ruanchaves-portuguese-text-simplification.hf.space)
+- Demo: [Portuguese Textual Entailment](https://ruanchaves-portuguese-textual-entailment.hf.space)
 
 ### **Labels**:
 * 0 : There is no entailment between premise and hypothesis.   
@@ -47,13 +46,6 @@ with torch.no_grad():
         print(f"{i+1}) Label: {l} Score: {np.round(float(s), 4)}")
 ```
 
-Output: 
-
-```
-1) Label: 1 Score: 1.0
-2) Label: 0 Score: 0.0
-```
-
 ## Citation 
 
 Our research is ongoing, and we are currently working on describing our experiments in a paper, which will be published soon. 
@@ -64,7 +56,7 @@ In the meanwhile, if you would like to cite our work or models before the public
 author = {Chaves Rodrigues, Ruan and Tanti, Marc and Agerri, Rodrigo},
 doi = {10.5281/zenodo.7781848},
 month = {3},
-title = {{eplm}},
+title = ,
 url = {https://github.com/ruanchaves/eplm},
 version = {1.0.0},
 year = {2023}