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SkillsMP は amd/Quark から 46 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
amd/Quark収集済み skill 46 件中 6 件を表示しています。
Install or verify the correct PyTorch build for a user's accelerator backend before Quark installation. Trigger for "install PyTorch", "pip install torch", "set up torch for ROCm", "set up torch for CUDA", "torch version mismatch", "CPU-only torch installed",…
原文の言語: 英語
End-to-end LLM accuracy evaluation on AMD ROCm (ROCm-only) — docker container setup OR host (no-docker) runtime, vLLM/SGLang/ATOM serving, lm-eval / lighteval / evalscope benchmarks. Use when the user wants to evaluate, benchmark, or compare an LLM's…
原文の言語: 英語
End-to-end Torch LLM PTQ recipe for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input): quantize, then validate, then evaluate accuracy, in one flow. Delegates the PTQ path (intake, planning, manifest, execution) to the…
原文の言語: 英語
Inspect a HuggingFace transformers / safetensors model and prepare metadata for Quark Torch PTQ planning. Use for model path validation, architecture detection, quantization target discovery, layer counting, risk assessment, or transformers compatibility…
原文の言語: 英語
Torch LLM PTQ workflow for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input). Use when the user wants a complete PTQ pipeline: model inspection, quantization planning, script generation, and optional execution. Stops at the…
原文の言語: 英語
Validate Quark Torch quantization output (HuggingFace safetensors + config.json) using four lightweight checks: auxiliary file copy alignment, excluded tensor MD5 byte-identity, config.json deep comparison after stripping quantization keys, and safetensors…
原文の言語: 英語