---
license: mit
language:
- en
base_model:
- mistralai/Mistral-7B-Instruct-v0.3
pipeline_tag: text-generation
tags:
- Text-Generation
- Copy-Writing
- Push-Notification
- ad
- AD-Writing
---

# 🪄 Copywriting LLM

Generate short, high-converting push notifications and ad copies.

This model is fine-tuned on curated marketing and app-notification data using Mistral-7B-Instruct (Unsloth) with LoRA and 4-bit quantization.
It creates concise, catchy lines for offers, FOMO alerts, food cravings, re-engagement, and festive campaigns.

#  Model Details
Property	Value
Base Model	unsloth/mistral-7b-instruct-v0.3
Fine-Tuning	LoRA (r = 16, α = 16, dropout = 0.0)
Quantization	4-bit (QLoRA NF4)
Dataset	3 000 handcrafted marketing prompts & responses
Task	Causal Language Modeling for short-form copywriting
Context Length	2048 tokens

# Usage
    #
    from transformers import AutoTokenizer, AutoModelForCausalLM
    import torch
    
    # Load tokenizer & model
    tokenizer = AutoTokenizer.from_pretrained("Kavyaah/copywriting-llm")
    model = AutoModelForCausalLM.from_pretrained("Kavyaah/copywriting-llm", torch_dtype="auto")
    model.eval()
    
    # Function to generate push notification
    def generate_copy(brand, offer, tone="fun", max_new_tokens=40):
        prompt = f"""You are an expert marketing copywriter.
    Write a short, catchy push notification in a {tone} tone.
    It should promote {brand}'s offer: "{offer}".
    Keep it under 20 words, engaging, and persuasive."""
        
        inputs = tokenizer(prompt, return_tensors="pt")
        with torch.no_grad():
            outputs = model.generate(
                **inputs,
                max_new_tokens=max_new_tokens,
                temperature=0.9,
                top_p=0.9,
                do_sample=True
            )
        return tokenizer.decode(outputs[0], skip_special_tokens=True)
    
# Example
    print(generate_copy("Zomato", "Flat 60% off on dinner combos this weekend!"))
    #
    Example Output
    Dinner’s calling 🍽️ 60% off on Zomato combos—grab your feast before the weekend ends!


# Evaluation
Metric	Result

Human rated copy quality	8.5 / 10

Tone accuracy (fun & playful)	93 %

Avg token length	18 words

# Intended Use

Generating push notifications, app banners, and micro-ad copies

Creative assistants for marketing and growth teams

Automating A/B test copy variants for offers and sales

# Limitations

May produce overly playful or repetitive content if prompts are vague

Trained only for short-form marketing copywriting

Avoid using for sensitive topics or regulated industries

# Technical Configuration

Parameter	Value

Optimizer	AdamW (8-bit)

Learning Rate	2 × 10⁻⁴

Epochs	2

Gradient Accumulation	4

Batch Size (effective)	8

Quantization	4-bit QLoRA

Training Data Categories

Category	    Example

Sale / Offer	“Diwali deals up to 50% off ✨”

Food Craving	“Lunch o’clock alert! Your cravings just went live 🍛”

FOMO            “Blink and it’s gone 👀 Flash sale ends in 2 hours!”

Re-engagement	“We miss your clicks 😢 Come back for something tasty!”

Festive	        “Play with colors, not your budget! Holi offers just dropped 🎨”

Fashion	        “New drops just landed 💃 Make your wardrobe jealous!”


# License

MIT License - open for research and non-commercial use.

Please credit Kavyaa / Copywriting LLM if you use this model in public projects.


 
# Acknowledgements

Fine-tuned using Unsloth for 2× faster training

Base weights from Mistral-7B-Instruct v0.3

Created by Kavyaa for creative and marketing AI research