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README.md

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+---
+pipeline_tag: zero-shot-classification
+tags:
+- zero-shot-classification
+- nli
+language:
+- es
+datasets:
+- hackathon-pln-es/nli-es
+widget:
+- text: "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo"
+  candidate_labels: "cultura, sociedad, economia, salud, deportes"
+---
+
+
+# A zero-shot classifier based on bertin-roberta-base-finetuning-esnli
+
+This is a [sentence-transformers](https://www.SBERT.net) model trained on a
+collection of NLI tasks for Spanish. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
+
+Based around the siamese networks approach from [this paper](https://arxiv.org/pdf/1908.10084.pdf).
+
+## Usage (HuggingFace Transformers)
+Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
+
+```python
+from transformers import pipeline
+classifier = pipeline("zero-shot-classification", 
+                       model="hackathon-pln-es/bertin-roberta-base-zeroshot-esnli")
+
+classifier(
+    "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo",
+    candidate_labels=["cultura", "sociedad", "economia", "salud", "deportes"],
+    hypothesis_template="Este ejemplo es {}."
+)
+```
+
+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.**
+
+## Training
+The model was trained with the parameters:
+
+**Dataset**
+
+We used a collection of datasets of Natural Language Inference as training data:
+ - [ESXNLI](https://raw.githubusercontent.com/artetxem/esxnli/master/esxnli.tsv), only the part in spanish
+ - [SNLI](https://nlp.stanford.edu/projects/snli/), automatically translated
+ - [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/), automatically translated
+
+The whole dataset used is available [here](https://huggingface.co/datasets/hackathon-pln-es/ESnli).
+
+## Full Model Architecture
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 514, 'do_lower_case': False}) with Transformer model: RobertaModel 
+  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
+)
+```
+
+## Authors
+
+- [Anibal Pérez](https://huggingface.co/Anarpego)
+- [Emilio Tomás Ariza](https://huggingface.co/medardodt)
+- [Lautaro Gesuelli](https://huggingface.co/Lautaro)
+- [Mauricio Mazuecos](https://huggingface.co/mmazuecos)