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I will fine tune your llm with lora for custom tasks
AI Engineer, Healthcare Automation Specialist
I'm an AI Engineer specializing in healthcare automation — I build systems that help small independent practices reduce claim denials, automate billing workflows, and save staff time using AI.
My wor...
About this Gig
Generic LLMs give generic answers. If you need a model that reliably classifies, extracts, or formats YOUR data fine-tuning beats prompting for narrow, repeatable tasks.
I fine-tune open-source LLMs (Qwen, Llama, Gemma, Mistral) using LoRA/QLoRA the parameter-efficient method teams use when full retraining isn't affordable. My portfolio includes a documented case study comparing a LoRA-tuned model against a paid API on a real classification task, with verified accuracy, latency, and cost numbers not just a demo.
What you get:
- A model fine-tuned on YOUR data for YOUR exact task
- An honest evaluation report accuracy, not vibes
- The trained adapter, ready to deploy
- Clear docs, no lock-in
Why work with me:
Most sellers show a demo. I show a real engineering case study: dataset, benchmarks, a trade-off analysis (accuracy vs. cost vs. latency vs. privacy) the thinking that matters once this hits production.
Best for: text classification, structured extraction, categorization, tone/format adaptation. Not for teaching new facts (that's RAG) I'll tell you honestly which fits.
Message me your task and a data sample (even 20-30 examples) and I'll advise for free first.
Programming Language:
Python
Data Type:
Text
AI Engine:
Llama
•
Other
FAQ
What data do I need to provide?
A spreadsheet or JSON file of input-output examples for your task. Even 20-30 samples is enough for me to assess feasibility before you order. More examples (200-2,000+) generally means better accuracy.
Which models can you fine-tune?
Open-source models like Qwen, Llama, Gemma, and Mistral, in sizes that fit free-tier GPU compute (roughly up to 7-8B parameters with QLoRA). I'll confirm the right model size for your task and data volume before starting.
Is this fine-tuning or just prompt engineering?
Real fine-tuning: I train LoRA/QLoRA adapters that update the model's actual weights on your data, not just crafted prompts. You receive the trained adapter file itself, not a prompt template.
Will I own the fine-tuned model?
Yes. You receive the trained adapter and full usage rights. It's yours to deploy, host, or hand to your own team.
Can you compare fine-tuning against just using an API?
Yes, in the Standard and Premium packages I benchmark your fine-tuned model against prompting a hosted API on the same task, covering accuracy, latency, and cost so you can see which approach actually fits.
What if my dataset is small or messy?
Message me first with a sample. I'll tell you honestly whether your data is enough, and help you think through what to collect if not, before you place an order.
Do you provide the training code?
Yes, all packages include the training script and full documentation, so you're not dependent on me for future retraining.
How long does delivery take?
Basic: 5 days. Standard: 7 days. Premium: 10 days. Turnaround depends on dataset size and any back-and-forth on requirements.
