:rocket: Deploy model

README.md

@@ -1,13 +1,13 @@
----
-title: Practica 8 Sec2sec
-emoji: 🦀
-colorFrom: green
-colorTo: blue
-sdk: gradio
-sdk_version: 4.31.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Practica 8 Sec2sec
+emoji: 🐨
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 3.18.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,19 @@
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import gradio as gr
+import torch
+
+# Cargar el modelo
+model_name = "nlmaldonadog/mbart-clarification-P8"
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def predict(text):
+    inputs = tokenizer(text, return_tensors='pt')
+    outputs = model(**inputs)
+    probs = torch.nn.functional.softmax(outputs.logits, dim=-1)
+    return {'negative': float(probs[0][0]), 'neutral': float(probs[0][1]), 'positive': float(probs[0][2])}
+
+texto = gr.inputs.Textbox(lines=2, placeholder='Escribe aquí...')
+
+# Creamos la interfaz y la lanzamos. 
+gr.Interface(fn=predict, inputs=texto, outputs=gr.outputs.Label()).launch(share=False)

requirements.txt

@@ -0,0 +1,3 @@
+fastai
+toml
+transformers