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--- |
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pipeline_tag: zero-shot-classification |
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tags: |
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- zero-shot-classification |
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- nli |
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language: |
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- es |
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datasets: |
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- hackathon-pln-es/nli-es |
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widget: |
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- text: "Para detener la pandemia, es importante que todos se presenten a vacunarse." |
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candidate_labels: "salud, deporte, entretenimiento" |
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--- |
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# A zero-shot classifier based on bertin-roberta-base-spanish |
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This model was trained on the basis of the model `bertin-roberta-base-spanish` using **Cross encoder** for NLI task. A CrossEncoder takes a sentence pair as input and outputs a label so it learns to predict the labels: "contradiction": 0, "entailment": 1, "neutral": 2. |
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You can use it with Hugging Face's Zero-shot pipeline to make **zero-shot classifications**. Given a sentence and an arbitrary set of labels/topics, it will output the likelihood of the sentence belonging to each of the topic. |
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## Usage (HuggingFace Transformers) |
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The simplest way to use the model is the huggingface transformers pipeline tool. Just initialize the pipeline specifying the task as "zero-shot-classification" and select "hackathon-pln-es/bertin-roberta-base-zeroshot-esnli" as model. |
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```python |
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from transformers import pipeline |
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classifier = pipeline("zero-shot-classification", |
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model="hackathon-pln-es/bertin-roberta-base-zeroshot-esnli") |
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classifier( |
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"El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo", |
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candidate_labels=["cultura", "sociedad", "economia", "salud", "deportes"], |
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hypothesis_template="Esta oración es sobre {}." |
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) |
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``` |
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The `hypothesis_template` parameter is important and should be in Spanish. **In the widget on the right, this parameter is set to its default value: "This example is {}.", so different results are expected.** |
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## Training |
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We used [sentence-transformers](https://www.SBERT.net) to train the model. |
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**Dataset** |
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We used a collection of datasets of Natural Language Inference as training data: |
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- [ESXNLI](https://raw.githubusercontent.com/artetxem/esxnli/master/esxnli.tsv), only the part in spanish |
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- [SNLI](https://nlp.stanford.edu/projects/snli/), automatically translated |
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- [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/), automatically translated |
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The whole dataset used is available [here](https://huggingface.co/datasets/hackathon-pln-es/nli-es). |
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## Authors |
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- [Anibal Pérez](https://huggingface.co/Anarpego) |
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- [Emilio Tomás Ariza](https://huggingface.co/medardodt) |
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- [Lautaro Gesuelli Pinto](https://huggingface.co/Lautaro) |
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- [Mauricio Mazuecos](https://huggingface.co/mmazuecos) |
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