KDFlow – Streamline LLM Knowledge Distillation for Faster Model Tuning
From the repo · “A user-friendly & efficient knowledge distillation framework for LLMs, supporting off-policy, on-policy (OPD), cross-tokenizer, multimodal, and on-policy self-distillation.”
KDFlow is a framework that allows startup founders to efficiently perform knowledge distillation on large language models, transferring knowledge from a teacher model to a student model.
- •When you have a large pre-trained language model and want to reduce its size while preserving its performance
- •When you need to adapt a language model to a specific domain or task with limited training data
- •When you want to improve the efficiency of your language model deployment without sacrificing accuracy
python train.py --config config.py --teacher_model bert-base-uncased --student_model distilbert-base-uncased --dataset glue-mnli
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/kdflow && curl -fsSL https://workflowstacks.com/api/skills/kdflow/claude-skill -o ~/.claude/skills/kdflow/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
KDFlow – Streamline LLM Knowledge Distillation for Faster Model Tuning is a medium Python project (~12k lines across 93 code files, plus 1 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, MIT license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2pyproject.tomlDependencies and the commands it exposes
- 3kdflow/__init__.pyInside kdflow/ — the main logic begins here
- 4examples/cross_tokenizer_kd/run_qwen3_30b_a3b_to_llama3_2_3b_offpolicy.shA worked example — copy this to get going
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/kdflow && curl -fsSL https://workflowstacks.com/api/skills/kdflow/claude-skill -o ~/.claude/skills/kdflow/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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