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README.md ADDED
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+ ---
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+
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+ pipeline_tag: text-classification
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+ inference: false
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+ language: en
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+ tags:
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+ - transformers
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+
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+ ---
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+
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+ # Prompsit/paraphrase-roberta-es
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+
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+ This model allows to evaluate paraphrases for a given phrase.
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+
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+ We have fine-tuned this model from pretrained "PlanTL-GOB-ES/roberta-base-bne".
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+
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+ Model built under a TSI-100905-2019-4 project, co-financed by Ministry of Economic Affairs and Digital Transformation from the Government of Spain.
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+
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+ # How to use it
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+
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+ The model answer the following question: Is "phrase B" a paraphrase of "phrase A".
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+
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+ Please note that we're considering phrases instead of sentences. Therefore, we must take into account that the model doesn't expect to find punctuation marks or long pieces of text.
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+
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+ Resulting probabilities correspond to classes:
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+
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+ * 0: Not a paraphrase
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+ * 1: It's a paraphrase
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+
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+ So, considering the phrase "se buscarán acuerdos" and a candidate paraphrase like "se deberá obtener el acuerdo", you can use the model like this:
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+
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+ ```
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+
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+ import torch
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+
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+ from transformers import AutoTokenizer, AutoModelForSequenceClassification
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+ tokenizer = AutoTokenizer.from_pretrained("Prompsit/paraphrase-roberta-es")
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+ model = AutoModelForSequenceClassification.from_pretrained("Prompsit/paraphrase-roberta-es")
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+
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+ input = tokenizer('se buscarán acuerdos','se deberá obtener el acuerdo',return_tensors='pt')
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+ logits = model(**input).logits
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+ soft = torch.nn.Softmax(dim=1)
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+ print(soft(logits))
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+
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+ ```
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+
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+ Code output is:
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+
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+ ```
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+
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+ tensor([[0.2266, 0.7734]], grad_fn=<SoftmaxBackward>)
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+
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+ ```
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+
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+ As the probability of 1 (=It's a paraphrase) is 0.77 and the probability of 0 (=It is not a paraphrase) is 0.22, we can conclude, for our previous example, that "se deberá obtener el acuerdo" is a paraphrase of "se buscarán acuerdos".
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+
config.json ADDED
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+ {
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+ "_name_or_path": "PlanTL-GOB-ES/roberta-base-bne",
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+ "architectures": [
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+ "RobertaForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "Not Paraphrase",
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+ "1": "Paraphrase"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "Not Paraphrase": 0,
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+ "Paraphrase": 1
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.11.3",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 50262
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+ }
merges.txt ADDED
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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