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title: FoodExtract Fine-tuned LLM Structued Data Extractor v1
emoji: 📝➡️🍟
colorFrom: green
colorTo: blue
sdk: gradio
app_file: app.py
pinned: false
license: apache-2.0
---
"""
Fine-tuned Gemma 3 270M to extract food and drink items from raw text.
Input can be any form of real text (mostly focused on shorter image caption-like texts):
```
A truly eclectic and mouth-watering feast is laid out on the table, featuring savory favorites like crispy fried chicken,
a perfectly seared steak, and loaded tacos, complete with a side of creamy mayonnaise. To balance the heavier mains,
a vibrant assortment of fresh fruit sits nearby, including a crisp red apple, a tropical pineapple, and a scattering of
sweet cherries. Thirst-quenching options complete this extravagant spread, with a classic iced latte, an earthy matcha latte,
and a simple, refreshing glass of milk ready to be enjoyed.
```
And output will be a formatted string such as the following:
```
food_or_drink: 1
tags: fi, re
foods: tacos,red apple, pineapple, cherries, fried chicken, steak, mayonnaise
drinks: iced latte, matcha latte, milk
```
The tags map to the following items:
```
tags_dict = {'np': 'nutrition_panel',
'il': 'ingredient list',
'me': 'menu',
're': 'recipe',
'fi': 'food_items',
'di': 'drink_items',
'fa': 'food_advertistment',
'fp': 'food_packaging'}
```
* You can see walkthrough step by step code details at: https://www.learnhuggingface.com/notebooks/hugging_face_llm_full_fine_tune_tutorial
* See the fine-tuning dataset: https://huggingface.co/datasets/mrdbourke/FoodExtract-1k
* See the fine-tuned model: https://huggingface.co/mrdbourke/FoodExtract-gemma-3-270m-fine-tune-v1
"""
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