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$
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I will fine tune your open source llm on your dataset dataset
prashant chavan
About this gig
Need an open-source LLM that follows your task more consistently? I fine-tune compatible Llama, Qwen, Mistral, and other open-weight models on your dataset using LoRA or QLoRA. I compare the tuned model with the original on held-out examples.
Good fits: structured output, classification, extraction, domain style, and repeatable instructions. For facts that change often, I can advise whether RAG is a better fit.
Depending on your package, I deliver:
Dataset review, formatting, and a train/test split
One agreed model and scoped training workflow
Base vs tuned evaluation with a clear results report
Adapter weights, training and inference code, and setup notes
One API deployment with Premium
Before ordering, send your task, a data sample, preferred model, and 5 ideal input-output examples. I will confirm feasibility, model license, hardware needs, and scope. GPU and hosting charges are separate. Results depend on data quality and are measured, not guaranteed.
Get to know prashant chavan
prashant chavan
AI Engineer , RAG Chatbots, AI Agents , LLM Fine Tuning
- FromIndia
- Member sinceJul 2023
- Avg. response time1 hour
Languages
English
I build practical AI solutions that help businesses automate customer support, qualify leads, and find accurate answers from their data.
I develop RAG chatbots using PDFs, websites, knowledge bases, and databases, plus AI agents and workflow automation with Python, LangChain, LangGraph, vector databases, and leading LLMs.
My focus is reliable answers, source citations, clean integrations, and clear handover. Projects can include source code, documentation, deployment support, and a recorded walkthrough.
My Portfolio
Other AI Development Services I Offer
FAQ
Can you fine-tune any open-source LLM?
I can assess Llama, Qwen, Mistral, and other compatible open-weight models. The model's license, architecture, hardware needs, and your data determine the approach. The listed packages cover one text model up to about 8B parameters; larger or unusual models get a custom quote.
What do you need from me?
A task description, representative dataset sample, target model if you have one, and 5 examples of ideal input and output. Please also show examples where the current model fails.
Will this teach the model current facts from my documents?
Fine-tuning works best for repeatable behavior, format, style, classification, or extraction. If the facts change regularly, retrieval from your current documents may be more suitable. I can advise after reviewing the task.
How will you prove improvement?
I compare the base and tuned model on examples excluded from training. The report includes the test size, task-appropriate measures, sample outputs, and limitations. I do not promise a fixed accuracy increase.
What files will I own?
You receive the agreed adapter weights, training/inference code, and handover material. Use of the base model remains subject to its license. Any deployment is set up in an agreed environment under your control.
Are GPU and hosting costs included?
No. I estimate them from the model, data volume, and deployment target before the order. You pay those providers directly through your account.
Can you deploy the tuned model?
Yes. Premium includes one scoped API endpoint. Send your preferred cloud or server details before ordering so I can confirm compatibility and ongoing running costs.
