Skill rating

Fine-tune MiniCPM5-1B into a LoRA adapter and convert it to a GGUF adapter that loads directly into llama.cpp / llama-server and the MiniCPM Desk Pet app's custom-LoRA upload. Use when the user wants

Run MiniCPM5-1B or MiniCPM5-2B with Hugging Face Transformers for one-shot Python generation on GPU (bfloat16) or CPU (float32). Use when the user wants a quick Python script, no server, no extra deps

Fine-tune MiniCPM5-1B or MiniCPM5-2B with ms-swift or Megatron-SWIFT. Use when the user mentions "ms-swift", "swift sft", "swift rlhf", or "megatron sft". MiniCPM5-1B uses the PyPI release with `--tem

Fine-tune MiniCPM5-1B with xtuner (mmengine config-driven SFT). Use when the user mentions "xtuner", "mmengine", InternLM's training framework, or wants config-file-driven training.

Pick the right fine-tuning framework for a MiniCPM5-1B base checkpoint and route to a framework-specific cookbook skill. Use when the user wants to SFT / LoRA / DPO / continue-pretrain MiniCPM5 and ha

Run MiniCPM5-1B or MiniCPM5-2B with llama.cpp using the released GGUF artifacts (F16 / Q8_0 / Q4_K_M). Use when the user wants CPU-only / consumer-GPU / cross-platform native deployment, asks for "lla

Fine-tune MiniCPM5-1B or MiniCPM5-2B with unsloth for tight-VRAM single-GPU LoRA / QLoRA. Use when the user wants "unsloth", "FastLanguageModel", QLoRA on a 24 GB consumer GPU, or asks for the smalles

Run MiniCPM5-2B or MiniCPM5-1B on-device with Google's LiteRT-LM runtime — the litert-lm CLI or its OpenAI-compatible server on a desktop, the Kotlin API or the AI Edge Gallery app on Android, the sam

Serve MiniCPM5-1B or MiniCPM5-2B via SGLang as an OpenAI-compatible HTTP server with RadixAttention prefix cache and built-in MiniCPM5 tool-call parsing. Use when the user asks for "SGLang", "RadixAtt

Fine-tune MiniCPM5-1B or MiniCPM5-2B with bare-metal TRL + PEFT, including assistant-only loss via a chat-template patch. Use when the user wants minimal Python, no YAML, full control, or asks for "TR

Serve MiniCPM5-1B or MiniCPM5-2B via vLLM as an OpenAI-compatible HTTP server. Use when the user wants high-throughput production serving on NVIDIA GPU, asks for "vLLM", "OpenAI server", "REST API for

Run MiniCPM5-1B or MiniCPM5-2B natively on Apple Silicon with Apple's MLX framework. Use when the user has an Apple Silicon Mac and asks for "MLX", "mlx_lm", "mlx_lm.convert", "mlx_lm.generate", or wa

Pick the right inference backend for a MiniCPM5-1B or MiniCPM5-2B checkpoint and route to a backend-specific cookbook skill. Use when the user wants to deploy / serve / chat-with / benchmark a MiniCPM

Fine-tune MiniCPM5-1B or MiniCPM5-2B with LLaMA-Factory (YAML-driven SFT / DPO / WebUI). Use when the user wants to fine-tune via LLaMA-Factory, llamafactory-cli, mentions YAML configs, WebUI, or asks

Deploy MiniCPM5-2B with vLLM on Huawei Ascend NPU using vLLM-Ascend. Use when the user mentions vLLM-Ascend, Ascend NPU, Huawei Ascend, CANN, torch_npu, davinci devices, or wants an OpenAI-compatible

Run MiniCPM5-1B or MiniCPM5-2B in LM Studio (desktop GUI) using either the GGUF runtime (cross-platform) or the MLX runtime (Apple Silicon, faster). Includes OpenAI-compatible local server. Use when t

Run MiniCPM5-1B or MiniCPM5-2B via Ollama on macOS / Linux laptop using the released GGUF. Use when the user wants "ollama run", "ollama pull", a Modelfile-driven setup, or one-line laptop deployment.