Custom Model Fine-Tuning & Knowledge Distillation
Domain-adapted LLMs fine-tuned on proprietary enterprise datasets using LoRA, QLoRA, and preference optimization (DPO/RLHF).
System Verification Benchmarks
Parameter Range
1B to 70B
Inference Cost Cut
70% reduction
Domain Accuracy
+34% uplift
Throughput Boost
3.5x faster
Executive Summary & Capabilities
Drastically reduce operational LLM inference costs while boosting specialized task accuracy. We distill teacher models into lightweight 7B-70B parameter open-weights models tailored specifically to your domain terminology and workflows.
Synthetic Data Pipeline
Automated data cleaning, deduplication, and high-quality synthetic instruction generation.
Parameter-Efficient Fine-Tuning
LoRA and QLoRA training techniques enabling rapid model iterations with minimal VRAM overhead.
Preference Optimization (DPO)
Direct Preference Optimization aligning model responses with corporate voice and safety rules.
Quantized vLLM Deployment
Optimized FP8 and INT4 quantization for maximum throughput on cost-efficient GPU clusters.
Deployment Readiness
Turnkey integration options
Architecture Specifications
Verified technical limits & implementation parameters
| Parameter | Technical Detail | Standard Level |
|---|---|---|
| Supported Frameworks | PyTorch, HuggingFace, Unsloth, DeepSpeed | Latest |
| Alignment Methods | DPO, KTO, PPO, Direct Supervised Tuning | Custom |
| Serving Engine | vLLM / TensorRT-LLM with PagedAttention | High-Concurrency |
| Weights Ownership | 100% Client-Owned Private Artifacts | Zero Lock-in |
Production Execution Pipeline
Dataset Auditing
Sanitizes, deduplicates, and structures enterprise corpus into instruction pairs.
Supervised Fine-Tuning
Executes multi-GPU distributed training with gradient accumulation.
Alignment & Evaluation
Applies DPO alignment and tests model against customized domain benchmark suites.
Quantized Serving
Compiles model weights for low-latency vLLM serving on dedicated GPU instances.
Ready to Deploy Custom Model Fine-Tuning & Knowledge Distillation?
Speak with our AI principal engineers to review your existing infrastructure and receive a tailored implementation architecture plan.