LLM Training and Fine Tuning
LLM training and fine tuning for production AI teams
Inwire.ai supports LLM training, LLM fine tuning, dataset preparation, evaluation, and deployment-ready delivery for teams building domain-specific language models on private enterprise data.
Fast answer
Inwire.ai helps teams turn private data into production-ready LLMs by combining data cleaning, data labeling, LoRA and QLoRA fine tuning, evaluation, benchmark reporting, deployment packaging, and ModelOps governance.
Production outcomes
Prepare high-quality instruction, classification, extraction, and domain datasets.
Fine tune open-source and private LLMs with LoRA, QLoRA, or full fine tuning workflows.
Evaluate trained models and deliver optimized artifacts for governed production deployment.
Training starts with clean, labeled data
Inwire.ai helps teams clean, label, deduplicate, normalize, and validate training data so fine tuning work is based on signal instead of noisy raw records.
Fine tuning methods matched to the model
Choose full fine tuning, LoRA, QLoRA, or parameter-efficient methods based on model size, domain requirements, budget, and deployment constraints.
Evaluation before deployment
Benchmark accuracy, safety, latency, throughput, and regression behavior before trained models are promoted into production AI model deployment workflows.
What inwire.ai can run and optimize
Clean, label, deduplicate, normalize, and quality-score instruction and domain datasets.
Run LoRA, QLoRA, full fine tuning, supervised fine tuning, and evaluation workflows.
Benchmark quality, safety, latency, throughput, and regression behavior before deployment.
Deliver trained artifacts with quantization guidance and deployment configs for vLLM, SGLang, TensorRT-LLM, Triton, and TGI.
Questions teams ask before rollout
What is LLM fine tuning?
LLM fine tuning adapts a foundation model to a specific domain or task using curated examples, evaluation sets, and training methods such as LoRA, QLoRA, or full fine tuning.
Does Inwire.ai help with training data preparation?
Yes. Inwire.ai supports data cleaning, data labeling, validation, deduplication, quality scoring, and formatting for LLM training and fine tuning.