Moves repetitive LLM tasks like classification, extraction and tool calling onto small models that run locally. It builds training data from your logs, fine-tunes on your own machine, and checks the small model against held-out data before you ship it.
@rchazBuild a training dataset for fine-tuning, distillation, or continued pretraining. Use when the user wants to turn logs/CSV/JSONL…
@rchazThe tunelab front door — decides whether a task needs fine-tuning at all, by running EXPERIMENTS on the user's data, not just…
@rchazEvaluate a fine-tuned, distilled, or continued-pretrained model with held-out test discipline — the honest scoreboard at the end…
@rchazThe tunelab capstone — drives a self-improving AI system. Use when the user wants a deployed model/cascade/workflow to keep…
@rchazDrive a local MLX-LM training run on Apple Silicon (LoRA/QLoRA, full fine-tuning, CPT) after tune-decide has validated a Level…
@rchazIs this you? Claim your profilePut a plugin at the top of Plugins, from $9
