AI & LLM Engineering · By amd

Inspects and tunes the shared-vs-dedicated memory split on AMD Ryzen APUs with unified memory (UMA) so larger LLMs and image-gen models fit on the iGPU, or so reserved GPU memory is returned to the…

amd/skills

Turns a natural-language description of routing intent into a valid Lemonade collection.router policy JSON.

amd/skills

Build the standalone ZenDNN native library (zendnnl) from source with the alternate compute backends OFF (no oneDNN, libxsmm, parlooper, fbgemm), keeping AOCL DLP, which is the GEMM backend zendnnl…

amd/ZenDNN

Mines local Claude Code session transcripts with a deterministic Python pipeline to show what the agent is actually used for, how often it fails and what it costs.

amd/gaia

Makes this agent generate images, transcribe audio, and synthesize speech on the user's own machine through a local Lemonade Server instead of a paid cloud API.

amd/skills

Benchmarks AMD's GAIA agent against Claude Code and across models on quality, honesty, steps, tokens, time and real cost, using gaia eval tasks.

amd/gaia

Serves AI models on AMD Instinct GPU hardware using vLLM. An agent skill from amd/skills.

amd/skills

Build vLLM (CPU) end-to-end with the oneDNN + ZenDNN (zen64) backend via direct integration (NO zentorch).

amd/ZenDNN

Run, resume, monitor, diagnose, and report Quark Quant-Perf workflows for PyTorch and HuggingFace transformers models.

amd/Quark

Serves an LLM on a supported AMD EPYC server CPU using vLLM with zentorch, in Docker, Podman, or conda.

amd/skills

Author a new ShapeShifter graph-transformation pass for AMD Quark (ONNX or PyTorch) so it conforms to the pass framework's conventions and auto-registers.

amd/Quark

Walks through scaffolding, writing and testing a new GAIA agent as a Python class with the SDK, from the base Agent subclass to registered tool methods.

amd/gaia

Autonomously optimizes end-to-end LLM inference throughput on AMD Instinct GPUs and reports a validated gain, using the Hyperloom multi-agent optimizer.

amd/skills

Collect and normalize environment facts (OS, Python, GPU, CUDA/ROCm, container state) before Quark installation or PTQ planning.

amd/Quark

Benchmarks LLM inference and drives GPU kernel optimization with Magpie.

amd/skills

Install or verify the AMD Quark package and its dependencies.

amd/Quark

L3 recipe that runs quark.onnx.AutoSearchPro end-to-end on a user .onnx model: intake → preset selection (or custom search space) → calibration / eval data reader → standalone autosearch script…

amd/Quark

Orchestrates modular PyTorch profiler trace analysis with TraceLens: generates perf reports, prepares category data, runs system-level and compute-kernel subagents in parallel, validates outputs…

amd/skills

Diagnose failed Quark ONNX installation, calibration, quantization, custom-op compilation, or export attempts.

amd/Quark

Embeds one of this repo's pre-built hub agents (under hub/agents/) into a developer's own application.

amd/gaia

Integrates local AI capabilities into applications using Embeddable Lemonade.

amd/skills

A skill your agent uses when integrating the @amd-gaia/agent-email npm package — embedding the GAIA email agent (a local triage/draft/send sidecar) into a Node, TypeScript, or Electron app.

amd/gaia

Install or verify the correct ONNX Runtime build (and the onnx package) for a user's accelerator backend before Quark's ONNX-to-ONNX flow.

amd/Quark

Inspect a target ONNX model and prepare metadata for Quark ONNX PTQ planning.

amd/Quark

End-to-end ONNX PTQ workflow for AMD Quark — from a .onnx file (and calibration data) to a quantized .onnx output.

amd/Quark

Build a Quark ONNX PTQ quantization plan from modelanalysis.json and user intent.

amd/Quark

Validate Quark ONNX quantization output using four lightweight checks: auxiliary file copy alignment, expected non-quantized initializer MD5 byte-identity (inline rawdata + external-data byte…

amd/Quark

Route Quark ONNX user goals to the correct atomic skill. An agent skill from amd/Quark.

amd/Quark

Apply existing ShapeShifter graph passes to an .onnx model via the quark-cli shapeshifter CLI or a ShapeShifter YAML.

amd/Quark

Detect upstream Quark ONNX changes that affect the ONNX skill family and classify required updates.

amd/Quark

Partition an ONNX model graph into named functional subgraphs and emit a subgraphpartition.json file.

amd/Quark

Diagnose failed Quark installation, PTQ execution, script generation, or export attempts.

amd/Quark

Compare skill contracts and guidance against current Quark documentation and source entry points.

amd/Quark

Prepare export and downstream evaluation handoff for a planned or completed Quark PTQ run.

amd/Quark

Low-memory file2file quantization for very large safetensors LLMs that cannot be loaded whole.

amd/Quark

Install or verify the correct PyTorch build for a user's accelerator backend before Quark installation.

amd/Quark

L3 recipe that runs a Torch LLM PTQ end-to-end for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input): quantize → validate → evaluate.

amd/Quark

Torch LLM PTQ workflow for AMD Quark — from model selection to quantized output.

amd/Quark

Inspect a target model and prepare metadata for Quark PTQ planning.

amd/Quark

Build a Quark Torch LLM PTQ quantization plan from model analysis and user intent.

amd/Quark

Validate Quark quantization output using four lightweight checks: auxiliary file copy alignment, excluded tensor MD5 byte-identity, config.json deep comparison after stripping quantization keys, and…

amd/Quark

Route Quark user goals to the correct atomic skill or workflow.

amd/Quark

Route Quark user goals to the correct atomic skill or workflow.

amd/Quark

Detect upstream Quark changes that affect the skill system and classify required updates.

amd/Quark

Validate workspace shape, model paths, output directories, and repo structure before downstream Quark skills proceed.

amd/Quark

A skill your agent uses when integrating the @amd-gaia/gaia npm package — running GAIA's flagship agent, or embedding its local sidecar into a Node, TypeScript, or Electron app.

amd/gaia

Installs or verifies AMD Quark and ensures the selected Python environment has an accelerator-matched PyTorch.

amd/Quark

Runs an end-to-end AMD Quark post-training quantization workflow for PyTorch / Hugging Face LLMs: inspect a Hub or local model, choose a quantization plan, create reproducible artifacts, request…

amd/Quark