KDFlow: Simplify LLM Knowledge 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.
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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