metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- lora
- qlora
- script-writing
- ads
- youtube-shorts
- reels
- marketing
- content-creation
language:
- en
pipeline_tag: text-generation
SireIQ-Scripts 🧠✍️
SireIQ-Scripts is an instruction-tuned AI model for generating viral content scripts, including:
- Short-form video scripts (Reels, TikTok, Shorts)
- Marketing & ad copy
- Image/video storytelling scripts
- Hook-based social media content
This model is fine-tuned using LoRA on top of Mistral-7B-Instruct.
🔧 Model Details
- Base Model: mistralai/Mistral-7B-Instruct-v0.2
- Fine-tuning: LoRA / QLoRA
- Training Type: Instruction-following
- Framework: Hugging Face Transformers
- Environment: Single GPU (Colab / Ubuntu)
📥 How to Use
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
base_model = "mistralai/Mistral-7B-Instruct-v0.2"
lora_model = "your-username/SireIQ-Scripts"
tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(
base_model,
device_map="auto",
load_in_4bit=True
)
model = PeftModel.from_pretrained(model, lora_model)
prompt = """Write a viral Instagram reel script about AI replacing jobs."""
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))