| | --- |
| | license: mit |
| | language: |
| | - en |
| | base_model: |
| | - mistralai/Mistral-7B-Instruct-v0.2 |
| | pipeline_tag: text-generation |
| | library_name: transformers |
| | --- |
| | |
| | # 🎨 wrapbow.ai — Creative Copy & Ideation LLM |
| | **Powered by Mistral 7B | Tuned by Ashish Kumar** |
| |
|
| | `wrapbow.ai` is a domain-adapted LLM built on **Mistral-7B-Instruct-v0.2**, finely tuned to generate high-quality marketing, educational, and digital experience content. Designed for creators, marketers, startups, and educators — this model brings your prompts to life with flair and contextual intelligence. |
| |
|
| | --- |
| |
|
| | ## ✨ Primary Use Cases |
| |
|
| | - 🪄 **Creative Ad Banner & Copy Generation** |
| | Generate punchy headlines, CTAs, and ad taglines for static, HTML5, or video banners. |
| |
|
| | - 📢 **Promotional Messaging** |
| | Ideal for personalized offers, flash sale announcements, and event-based campaigns. |
| |
|
| | - 📚 **Quiz Question Generation** *(for platforms like [pinkslip.in](https://pinkslip.in))* |
| | Automatically generate skill-based, gamified quiz questions for job-seekers and upskilling portals. |
| |
|
| | - 🧠 **Prompt-Driven Content Ideation** |
| | Use it to brainstorm campaign themes, landing page hooks, or social content angles. |
| |
|
| | - 🖋️ **Brand Messaging & Positioning Lines** |
| | Write startup one-liners, value propositions, and feature-focused marketing blurbs. |
| |
|
| | - 🧩 **Use in EdTech, HRTech, and FinTech Landing Pages** |
| | Helps founders auto-generate customized landing copy for high conversion across sectors. |
| |
|
| | --- |
| |
|
| | ## ✅ Base Model |
| |
|
| | - [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) |
| |
|
| | --- |
| |
|
| | ## 💡 Example Usage (Python) |
| |
|
| | ```python |
| | from transformers import AutoTokenizer, AutoModelForCausalLM |
| | |
| | tokenizer = AutoTokenizer.from_pretrained("ashishkummar/wrapbow.ai", trust_remote_code=True) |
| | model = AutoModelForCausalLM.from_pretrained("ashishkummar/wrapbow.ai", trust_remote_code=True) |
| | |
| | prompt = "Generate a banner line for 50% discount on women's fashion" |
| | inputs = tokenizer(prompt, return_tensors="pt") |
| | outputs = model.generate(**inputs, max_new_tokens=50) |
| | print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
| | ``` |
| |
|
| | --- |
| |
|
| | ## 🔓 License |
| |
|
| | MIT — free to use, remix, and build upon. |
| |
|
