I will fine tune your llm with lora qlora on custom data
AI Engineer and LLM Fine Tuning, RAG, AI Chatbots and Agents
About this Gig
Need to fine-tune an LLM for your business, product, or specific task?
I will fine-tune your LLM on your custom dataset using LoRA, QLoRA, PEFT, and supervised fine-tuning (SFT) to improve task-specific behavior, responses, formatting, and instruction following.
I work with popular open-source models including Llama, Mistral, Qwen, Gemma, Phi, and other compatible Hugging Face models.
What I can provide:
- LLM fine-tuning with LoRA / QLoRA
- Custom dataset preparation and formatting
- Instruction and supervised fine-tuning
- Domain-specific model customization
- Model evaluation and testing
- Fine-tuned model or LoRA adapter
- Training configuration and inference setup
- Source code and training files
Your model can be customized for customer support, classification, structured responses, instruction following, professional writing, and other specialized tasks.
If you're unsure whether fine-tuning or RAG is right for your project, I can help you choose the appropriate approach.
Send me your model, dataset, and requirements before ordering so I can review the project and recommend the right solution.
Programming Language:
Python
Data Type:
Text
AI Engine:
Llama
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Other
My Portfolio
FAQ
Which LLMs can you fine-tune?
I can fine-tune compatible models such as Llama, Mistral, Qwen, Gemma, Phi, and other open-source LLMs.
Can you prepare my dataset?
Yes. I can clean, format, validate, and prepare your dataset for fine-tuning.
Do you support LoRA and QLoRA?
Yes. I specialize in parameter-efficient fine-tuning using LoRA and QLoRA.
Can you fine-tune 3B, 7B, or larger models?
Yes, depending on the model, dataset, training method, and available GPU resources.
Will fine-tuning give my model new knowledge?
Fine-tuning mainly teaches behavior, patterns, style, and task-specific responses. RAG is better for changing knowledge.
Can you evaluate the fine-tuned model?
Yes. Evaluation can be included to compare model performance before and after fine-tuning.
Can you deploy the fine-tuned model?
Yes. Deployment or inference setup can be included depending on the package and infrastructure.
Should I use fine-tuning or RAG?
It depends on your goal. I can review your project and recommend the more suitable approach.
