arcee-ai/DistillKit

Health v2 · maintenance only

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1047 stars · 139 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DistillKit is an open-source Python toolkit for knowledge distillation of large language models, supporting both online and offline distillation workflows. It includes an advanced logit compression system (polynomial approximation, quantization, and bit-packing) that makes large-scale offline distillation practical.

Use cases

• distill a large teacher LLM into a smaller student model
• run offline distillation from pre-captured teacher logits
• compress teacher logit datasets for large-scale distillation
• train a student model with KL divergence and other distillation losses
• capture teacher model outputs for later distillation training

When to choose

• you need to distill an LLM at scale using pre-captured teacher outputs
• you want battle-tested tooling that has powered production model releases
• you want flexible, composable distillation loss functions
• you already use the HuggingFace Transformers/TRL/Accelerate ecosystem

When to avoid

• you need general-purpose LLM fine-tuning rather than distillation
• you want a no-code or fully managed training service
• you lack GPU resources for model training
• you need distillation for non-language modalities

Facets

library · maturity active

llm-training machine-learning deep-learning gpu-computing large-language-models machine-learning deep-learning python knowledge-distillation logit-compression huggingface teacher-student-training offline-distillation gpu linux

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