I will fine tune llama 3, mistral, and custom llms on your dataset


About this gig
Does ChatGPT sound too generic? You don't need a bigger prompt. You need a Fine-Tuned Model trained on your specific data.
I am an AI Engineer specializing in Parameter-Efficient Fine-Tuning (PEFT). I train open-source models like Llama 3 & Mistral to master your unique domain, tone, and formatcreating a model that thinks exactly like your best employee.
What I Do:
- Data Prep: Cleaning & formatting your raw text/PDFs into training-ready JSONL.
- Training: Efficient fine-tuning using LoRA / QLoRA adapters.
- Optimization: Using Unsloth for 2x faster inference & lower memory usage.
- Validation: Testing against benchmarks to ensure quality.
Tech Stack:
- Models: Llama 3 (8B/70B), Mistral, Gemma, Phi-3.
- Tools: Hugging Face, PyTorch, Unsloth, A100 GPUs.
Use Cases:
- Support: Bots that answer exactly like your team.
- Professional: Summarize docs in specific Medical/Legal tones.
- Roleplay: Custom character personas.
- ️ PLEASE MESSAGE ME FIRST. Fine-tuning requires a good dataset. Let me analyze your data first to ensure this is the right solution for you.
Get to know Shubham K
Full Stack Dev, Backend Architect, AI Automation and API Specialist
- FromIndia
- Member sinceNov 2019
- Last delivery2 years
Languages
English, Hindi
Other AI Development Services I Offer
FAQ
How much data do I need?
For style transfer, 50-100 high-quality examples are enough. For new knowledge, you ideally need 500+ examples.
Will you host the model for me?
In the Premium package, I provide the deployment scripts (Docker/Ollama) so you can host it on AWS, RunPod, or your local machine. I do not pay for your monthly server costs.
What is the difference between RAG and Fine-Tuning?
RAG is for retrieving facts (like a search engine). Fine-Tuning is for learning behavior, style, and format. If you need the model to act a certain way, you need Fine-Tuning.
Do I own the model?
Yes. You get the model weights (adapters). You own 100% of the IP.
