First version

README.md

@@ -1,37 +1,9 @@
 ---
-title: Bertin Sqac
-emoji: 😻
-colorFrom: red
-colorTo: red
+title: BERTIN SQAC
+emoji: ❓
+colorFrom: yellow
+colorTo: orange
 sdk: gradio
 app_file: app.py
 pinned: false
 ---
-
-# Configuration
-
-`title`: _string_  
-Display title for the Space
-
-`emoji`: _string_  
-Space emoji (emoji-only character allowed)
-
-`colorFrom`: _string_  
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`colorTo`: _string_  
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`sdk`: _string_  
-Can be either `gradio` or `streamlit`
-
-`sdk_version` : _string_  
-Only applicable for `streamlit` SDK.  
-See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
-
-`app_file`: _string_  
-Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
-Path is relative to the root of the repository.
-
-`pinned`: _boolean_  
-Whether the Space stays on top of your list.

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+
+title = "BERTIN SQAC"
+description = "BERTIN large fine-tuned con el corpus SQAC (Spanish Question Answering Corpus)"
+article = "<p style='text-align: center'><a href='https://huggingface.co/nlp-en-es/bertin-large-finetuned-sqac'>BERTIN fine-tuned con el corpus SQAC (Spanish Question Answering Corpus)</a> | <a href='https://nlp-en-es.org'>NLP en ES 🤗</a></p>"
+examples = [
+    ["Mi nombre es María y vivo en Berlín.", "¿Dónde vivo?"],
+    ["La capital de Paraguay es Asunción.", "¿Cuál es la capital de Paraguay?"]
+]
+
+gr.Interface.load(
+    name="huggingface/nlp-en-es/bertin-large-finetuned-sqac",
+    inputs=[gr.inputs.Textbox(label="contexto"), gr.inputs.Textbox(label="pregunta")],   
+    outputs=gr.outputs.Textbox(label="respuesta"),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    enable_queue=True
+).launch()