Duplicate from igmarco/Practica2

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README.md

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+---
+title: Practica2
+emoji: 🌍
+colorFrom: green
+colorTo: yellow
+sdk: gradio
+sdk_version: 3.21.0
+app_file: app.py
+pinned: false
+duplicated_from: igmarco/Practica2
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from huggingface_hub import from_pretrained_fastai
+import gradio as gr
+# from fastai.vision.all import *
+from fastai.text.all import *
+
+
+
+# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
+repo_id = "igmarco/LSTM-text-classification"
+
+learner = from_pretrained_fastai(repo_id)
+labels = ['hate speech', 'offensive language', 'neither']
+
+# Definimos una función que se encarga de llevar a cabo las predicciones
+def predict(txt):
+    pred,pred_idx,probs = learner.predict(txt)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+    
+# Creamos la interfaz y la lanzamos. 
+gr.Interface(fn=predict, inputs=gr.Textbox(lines=2, placeholder="Text Here..."), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=False)

requirements.txt

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+fastai
+datasets
+toml