init

README.md

@@ -1,7 +1,7 @@
 ---
 title: Borrowing Detection Es
-emoji: 📈
-colorFrom: gray
+emoji: 🔍
+colorFrom: blue
 colorTo: purple
 sdk: gradio
 sdk_version: 3.19.1

app.py

@@ -0,0 +1,50 @@
+from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer
+import gradio as gr
+from spacy import displacy
+
+tokenizer = AutoTokenizer.from_pretrained("lirondos/anglicisms-spanish-mbert")
+model = AutoModelForTokenClassification.from_pretrained(
+    "lirondos/anglicisms-spanish-mbert"
+)
+nlp = pipeline("ner", model=model, tokenizer=tokenizer)
+
+diplacy_dict_template = {
+    "text": "But Google is starting from behind.",
+    "ents": [{"start": 4, "end": 10, "label": "ORG"}],
+    "title": None,
+}
+
+
+def infer(input_text):
+    displacy_ents = []
+    borrowings = nlp(input_text)
+    for borrowing in borrowings:
+        displacy_ent_dict = {
+            "start": borrowing["start"],
+            "end": borrowing["end"],
+            "label": borrowing["entity"],
+        }
+        displacy_ents.append(displacy_ent_dict)
+
+    displacy_dict_template = {"text": input_text, "ents": displacy_ents, "title": None}
+
+    html = displacy.render(displacy_dict_template, style="ent", page=True, manual=True)
+    
+    html = (
+        ""
+        + html
+        + ""
+    )
+    
+    return html
+
+
+demo = gr.Interface(
+    title="Borrowing Detection Español",
+    fn=infer,
+    inputs=gr.Text(),
+    outputs=gr.HTML(),
+    examples=["Buscamos data scientist para proyecto de machine learning."],
+)
+
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+transformers
+torch
+spacy