hyperparams
OfficialSmart guidance for tuning training hyperparameters.
Software Engineering#lora#hyperparameters#model-training#finetuning#learning-rate#batch-size#lr-schedule
Authorthinking-machines-lab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Helps ML engineers quickly select validated hyperparameters for fine-tuning language models, reducing trial-and-error and speeding up experiments.
Core Features & Use Cases
- Formula-based learning rate and LoRA calculations for common model families.
- Guided recommendations for batch sizes and schedules across supervised, RL, DPO, and distillation workflows.
- Scenario-driven guidance tailored to model size, architecture, and task requirements.
Quick Start
Use the hyperparams skill to derive learning rate, LoRA rank, batch size, and schedule recommendations for your model and training task.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: hyperparams Download link: https://github.com/thinking-machines-lab/tinker-cookbook/archive/main.zip#hyperparams Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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