I will build machine learning models and llms for your business

For LLM fine-tuning, you need a dataset of input-output pairs relevant to your task — for example, question-answer pairs, instruction-response pairs, or text classification examples. Minimum recommended: 500–1,000 examples for basic fine-tuning, 5,000+ for strong performance. I can help you structur

LoRA (Low-Rank Adaptation) and QLoRA (Quantized LoRA) are efficient fine-tuning techniques that adapt a large pre-trained model to your data using a fraction of the compute and cost of full fine-tuning. QLoRA in particular allows fine-tuning 7B–70B parameter models on consumer or cloud GPUs at low

Llama 3 (8B or 70B) is the best open-source choice for most tasks — strong performance, fully open weights, no licensing fees. Mistral 7B is excellent for lower compute budgets. GPT fine-tuning via OpenAI API is available for simpler classification tasks. I'll recommend the right model after reviewi

Yes — 100%. I deliver the model weights, training scripts, and evaluation results. The model is yours to deploy, modify, or distribute as you choose.

Before delivery, I run rigorous evaluation using standard metrics: accuracy and F1 for classification, BLEU/ROUGE for generation tasks, and custom benchmarks built from held-out examples of your own data. You receive a full evaluation report with the delivery.

Yes — I build the training pipeline so you can retrain or further fine-tune the model as your data grows. Premium includes automated retraining setup with monitoring for model drift.