quark-torch-llm-ptq-eval

quark-torch-llm-ptq-eval is an MLOps & model serving skill for AI agents, published by amd in the Quark repository on GitHub. Skillspace rates quark-torch-llm-ptq-eval D (64/100) and it passed the safety scan; the rating is based on static analysis only.

L3 recipe that runs a Torch LLM PTQ end-to-end for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input): quantize → validate → evaluate. Phase 1 delegates the full PTQ path (model intake → quantization planning → manifest generation → confirmed execution) to the `quark-torch-ptq` workflow; Phase 2 runs mandatory structural validation via `quark-torch-result-validator`; Phase 3 runs opt-in accuracy evaluation via `quark-torch-llm-eval`. Use when the user wants to "quantize and validate", "quantize and evaluate", "run PTQ end to end with accuracy check", "full PTQ pipeline including validation and eval", or "quantize Llama/Qwen/Mistral with FP8/INT4 and measure accuracy". For PTQ only (stop at the quantized output, no validation/eval), use `quark-torch-ptq`. Not for .onnx input models — use `quark-onnx-ptq` / `quark-onnx-autosearch-pro`.

Grade

D

Quality

64 / 100

Safety

Passed

GitHub stars

148

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