README.md

---
tags:
- text-generation
- gpt2
- recipes
- natural-language-generation
license: apache-2.0
---

# MinimalistRecipeTextGenerator

## Overview

This model is a fine-tuned version of the **GPT-2 (small)** language model, specifically trained to generate coherent and realistic short recipe texts. Given a prompt (e.g., "A quick chicken curry"), the model completes the text, often generating ingredient lists and basic instructions.

## Model Architecture

The model uses the standard **GPT-2 language modeling architecture**. 

1.  **Core:** A 12-layer, 768-dimensional transformer decoder stack.
2.  **Mechanism:** It operates based on attention mechanisms, predicting the next token in a sequence given all previous tokens.
3.  **Training:** Fine-tuned on a dataset of simple, short recipes, enabling it to learn the structural patterns of recipes (Title -> Ingredients -> Instructions).
4.  **Generation Parameters:** The `config.json` sets default generation parameters for high-quality output:
    * `do_sample`: True (for creative text generation)
    * `temperature`: 0.7 (controls randomness)
    * `max_length`: 256 (for short, complete recipes)

## Intended Use

This model is intended for creative and content generation purposes:

* **Creative Writing/Blogging:** Generating unique recipe ideas for food blogs or social media.
* **Data Augmentation:** Creating synthetic, but structurally correct, recipe texts for training other culinary-focused models.
* **Demonstration:** Serving as a basic example of fine-tuning GPT-2 on a domain-specific corpus.

### How to use

```python
from transformers import pipeline

generator = pipeline("text-generation", model="your_username/MinimalistRecipeTextGenerator") # Replace with actual hub path
prompt = "Recipe for a refreshing summer salad:"

output = generator(prompt, max_length=150, num_return_sequences=1, temperature=0.8)

print(output[0]['generated_text'])