Update README.md

README.md

@@ -1,3 +1,53 @@
 ---
+language: es
 license: gpl-3.0
+tags:
+- spaCy
+- Token Classification
+widget:
+- text: "Fue antes de llegar a Sigüeiro, en el Camino de Santiago."
+- text: "El proyecto lo financia el Ministerio de Industria y Competitividad."
+model-index:
+- name: es_spacy_ner_cds
+  results: []
 ---
+
+# Introduction
+
+spaCy NER model trained in the domain of tourism related to the Way of Saint Jacques. It recognizes four types of entities: location (LOC), organizations (ORG), person (PER) and miscellaneous (MISC).
+
+## Usage
+
+You can use this model with the spaCy *pipeline* for NER.
+
+```python
+import spacy
+from spacy.pipeline import merge_entities
+
+
+nlp = spacy.load("es_spacy_ner_cds")
+nlp.add_pipe('sentencizer')
+
+example = "Fue antes de llegar a Sigüeiro, en el Camino de Santiago. El proyecto lo financia el Ministerio de Industria y Competitiv
+idad."
+ner_pipe = nlp(example)
+
+print(ner_pipe.ents)
+for token in merge_entities(ner_pipe):
+    print(token.text, token.ent_type_)
+```
+
+## Dataset
+
+ToDo
+
+## Model performance
+
+entity|precision|recall|f1
+-|-|-|-
+PER|0.942|0.890|0.915
+ORG|0.869|0.688|0.768
+LOC|0.975|0.987|0.981
+MISC|0.854|0.757|0.803
+micro avg|0.963|0.958|0.961
+macro avg|0.910|0.831|0.867