Uploading our food not food classifier demo from a notebook!

README.md

@@ -1,12 +1,18 @@
 ---
-title: Learn Hf Food Not Food Text Classifier Demo
-emoji: 🌖
-colorFrom: green
-colorTo: blue
+title: Food Not Food Text Classifier
+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
+# 🍗🚫🥑 Food Not Food Text Classifier
+
+Small demo to showcase a text classifier to determine if a sentence is about food or not food.
+
+DistillBERT model fine-tuned on a small synthetic dataset of 250 generated [Food or Not Food image captions](https://huggingface.co/datasets/mrdbourke/learn_hf_food_not_food_image_captions).
+
+[Source code notebook](https://github.com/mrdbourke/learn-huggingface/blob/main/notebooks/hugging_face_text_classification_tutorial.ipynb).

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
+food_not_food_classifier = pipeline(task="text-classification",
+                                    model="tonicanada/learn_hf_food_not_food_text_classifier-distilbert-base-uncased",
+                                    device=torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu"),
+                                    top_k=1,
+                                    batch_size=32)
+
+# 3. Create a Gradio interface
+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 [small dataset of food and not food text](https://huggingface.co/datasets/mrdbourke/learn_hf_food_not_food_image_captions).
+
+See [source code](https://github.com/mrdbourke/learn-huggingface/blob/main/notebooks/hugging_face_text_classification_tutorial.ipynb).
+"""
+
+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=[["I whipped up a fresh batch of code, but it seems to have a syntax error."],
+                       ["A delicious photo of a plate of scrambled eggs, bacon and toast."]])
+)
+
+# 4. Launch the interface
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+torch
+transformers