memory-estimation

name	memory-estimation
description	Use when the user wants to estimate GPU memory (VRAM) requirements for a training configuration, check if a model will fit on their GPUs, or plan GPU allocation for training.
allowed-tools	["Bash(${CLAUDE_PLUGIN_ROOT}/scripts/th_estimate.sh:*)","Bash(${CLAUDE_PLUGIN_ROOT}/scripts/th_detect.sh:*)"]

GPU Memory Estimation

Estimate GPU VRAM requirements before committing to a training run.

Step 1: Check Environment

"${CLAUDE_PLUGIN_ROOT}/scripts/th_detect.sh"

If library=missing, tell the user to install training_hub first via the setup-guide skill.

Step 2: Run Estimation

Execute the estimation script with user-provided parameters or config defaults:

"${CLAUDE_PLUGIN_ROOT}/scripts/th_estimate.sh" $ARGUMENTS

Step 3: Present Results

Parse the JSON output and present clearly:

1. Memory estimates — Show low/mid/high VRAM estimates in GB
2. GPU fit — Report whether the configuration fits on the available GPU(s)
3. Recommendations — If memory is tight, suggest:
   • Reduce max_seq_len (e.g., 4096 -> 2048)
   • Reduce effective_batch_size
   • Switch to LoRA or QLoRA for lower memory
   • Add more GPUs for data parallelism

Estimation Methods

Method	For	Estimator
basic	SFT, GRPO	BasicEstimator
osft	OSFT	OSFTEstimator
lora	LoRA-SFT, LoRA-GRPO	LoRAEstimator
qlora	Quantized LoRA	QLoRAEstimator

If no method is specified, the script infers it from the configured algorithm.