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gemma4-tuning
gemma4-tuning contient 4 skills collectées depuis ghchinoy, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Guides agents on preparing datasets, running parameter-efficient LoRA fine-tuning, and tracking telemetry metrics using the mlxtune CLI on Apple Silicon. Use when an agent wants to fine-tune standard Gemma 4 base models on text instructions.
Guides agents on exporting fine-tuned Gemma models to multi-format mobile runtimes, comparing memory and hardware target characteristics, and implementing dynamic sandbox download workflows.
Guides agents on preparing multimodal datasets in interleaved ChatML format, executing audio/vision fine-tuning with mlx-vlm, targeting specific layers, and performing key-sanitized weights fusion to avoid silent blank weights loading.
Guides agents on fine-tuning Gemma 4 Quantization-Aware Training (QAT) unquantized checkpoints, maintaining mathematical alignment during LoRA, and exporting to GGUF using strict q4_0 parameters to avoid post-training quantization drift on edge devices.