Uploading our food not food classifier demo from a notebook!

README.md

@@ -1,12 +1,16 @@
 ---
-title: Learn Hf Spanish Sentence Classification By School Subject Demo
-emoji: 📚
-colorFrom: gray
-colorTo: gray
+title: Clasificador de asignaturas
+emoji: 📚🔍
+colorFrom: blue
+colorTo: yellow
 sdk: gradio
-sdk_version: 5.5.0
 app_file: app.py
 pinned: false
+license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 📚🔍 Clasificador de asignaturas
+
+Pequeña demo que clasifica las frases según si se refieren a asignaturas escolares (ejemplo: matemáticas, religión, etc).
+
+DistillBERT model fine-tuned on a small synthetic dataset of 250 generated [Frases ejemplo](https://huggingface.co/datasets/tonicanada/learn_hf_spanish_sentence_classification_by_school_subject).

app.py

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+# 1. Import the required libraries
+import torch
+import gradio as gr
+
+from typing import Dict
+from transformers import pipeline
+
+# 2. Define our function to use with our model
+spanish_sentence_classification_by_school_subject_pipeline = pipeline(task="text-classification",
+                                    model="tonicanada/learn_hf_spanish_sentence_classification_by_school_subject",
+                                    top_k=1,
+                                    device="cuda" if torch.cuda.is_available() else "cpu",
+                                    batch_size=32)    
+
+# 3. Create a Gradio interface
+description = """
+Un clasificador de texto que indica a qué asignatura se refiere la frase. 
+
+Fine-tuned from [DistilBERT](https://huggingface.co/distilbert/distilbert/distilbert-base-multilingual-cased) on a [small dataset of food and not food text](https://huggingface.co/datasets/mrdbourke/learn_hf_food_not_food_image_captions).
+"""
+
+demo = gr.Interface(
+    fn = spanish_sentence_classification_by_school_subject_pipeline,
+    inputs = "text",
+    outputs=gr.Label(num_top_classes=10),
+    title="📚🔍 Clasificador de asignaturas",
+    description=description,
+    examples=[["Matemáticas: 5 al cuadrado es 25"],
+                       ["Geografía: París es la capital de Francia"]])
+
+
+# 4. Launch the interface
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+torch
+transformers