| --- |
| 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 |
|
|
| ```python |
| 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)) |
| |
