Edge Distillation with Multi-Stage Tuning Pipeline for SLMs

Engineer a high-fidelity SLM for interactive persona by distilling linguistic patterns from frontier models (GPT 5.4 mini).

unslothtrltransformersggufvllmsagemakerboto3openai

Primary Features

Distill latent reasoning and Chain-of-Thought (CoT) capabilities from GPT-5.4 into a 3B model.
Engineer multi-stage tuning pipeline - SFT for grounding, RKD for logic, and DPO for stylistic parity.
Standardize input/output schemas using chat templates.
Implement 4-bit quantization (GGUF) to balance VRAM efficiency and perplexity for edge hardware.
Deploy via AWS SageMaker LMI/vLLM engine for paged-attention concurrency and real-time streaming.

Digital_Clone_ver1.0

Architected by Kuriko IWAI

Kuriko IWAI

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Kuriko IWAI, "Edge Distillation with Multi-Stage Tuning Pipeline for SLMs" in Kernel Labs

https://kuriko-iwai.com/labs/digital-clone-edge-distillation

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