Upload food not food text classifier demo from notebook

README.md

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 ---
-title: Learn Hf Food Not Food Text Classifier Demo
-emoji: 🏃
-colorFrom: indigo
-colorTo: gray
+title: Food Not Food Text Classifier
+emoji: 🍔🚫🍰
+colorFrom: yellow
+colorTo: red
 sdk: gradio
-sdk_version: 5.25.2
+sdk-version: 5.25.2
 app_file: app.py
 pinned: false
+license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🍔🚫🍰 Food or Not Food Text Classifier
+
+Demo to showcase a text classifier to determine if a sentence is about food or not food. 
+
+[DistilBERT](https://huggingface.co/distilbert/distilbert-base-uncased) model fine-tuned on a small [synthetic dataset]((https://huggingface.co/datasets/mrdbourke/learn_hf_food_not_food_image_captions)) of 250 generated food/not_food image captions. 

app.py

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+# Import required packages
+import torch
+import gradio as gr
+
+from typing import Dict
+from transformers import pipeline
+
+# Define a function to use the model
+def food_not_food_classifier(text: str) -> Dict[str, float]:
+
+  # Set up food not food text classifier
+  food_not_food_classifier_pipeline = pipeline(task="text-classification",
+                                      model="karenwky/learn_hf_food_not_food_text_classifier_distilbert-base-uncased",
+                                      batch_size=32,
+                                      device="cuda" if torch.cuda.is_available() else "cpu",
+                                      top_k=None)
+
+  # Get the output from the pipeline
+  outputs = food_not_food_classifier_pipeline(text)[0]
+
+  # Format output for Gradio
+  output_dict = {}
+  for item in outputs:
+    output_dict[item["label"]] = item["score"]
+
+  return output_dict
+
+# Create a Gradio interface with detilas about the app
+description = """
+A text classifier to determine if a sentence is about food or not food.
+
+Fine-tuned from [DistilBERT](https://huggingface.co/distilbert/distilbert-base-uncased) on a [LLM-generated dataset of food/not_food image captions](https://huggingface.co/datasets/mrdbourke/learn_hf_food_not_food_image_captions).
+"""
+
+demo = gr.Interface(
+    fn=food_not_food_classifier,
+    inputs="text",
+    outputs=gr.Label(num_top_classes=2),
+    title="🍔🚫🍰 Food or Not Food Text Classifier",
+    description=description,
+    examples=[["Today is a sunny day."],
+              ["Pineapple fried rice."]]
+)
+
+# Launch the interface
+if __name__ == "__main__":
+  demo.launch()

requirements.txt

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+gradio
+torch
+transformers