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Stable Diffusion Sd3
作者
Twin Geeks
· GitHub ↗
· v1.0.2
· MIT-0
211
总下载
2
收藏
2
当前安装
3
版本数
在 OpenClaw 中安装
/install stable-diffusion-sd3
功能描述
Stable Diffusion 3 and SD3.5 Large on Apple Silicon — generate Stable Diffusion images locally with DiffusionKit's MLX-native backend. SD3 Medium for fast St...
安全使用建议
This skill appears internally consistent with its goal of running Stable Diffusion locally, but before installing or running anything: (1) review the PyPI package 'ollama-herd' source and any 'uv tool' provider to ensure you trust them; (2) inspect any provided patch scripts (e.g., patch-diffusionkit-macos26.sh) before executing; (3) expect large downloads (2–8GB model weights) and significant RAM usage—run on an isolated or well-backed-up machine if concerned; (4) the router opens a local HTTP port (11435) — confirm it is bound only to localhost or properly firewalled if you do not want other LAN hosts to access it; (5) if you use private HuggingFace assets, verify whether authentication is needed and handle tokens separately; and (6) consider running installs in a virtualenv or dedicated environment to limit accidental system-wide changes.
能力评估
Purpose & Capability
Name/description (local Stable Diffusion on Apple Silicon, fleet routing) align with the instructions: examples use a local router on http://localhost:11435, recommend installing ollama-herd, diffusionkit, and mflux. Declared required binaries (curl/wget, optional python3/pip) match the documented commands. The metadata's configPaths (~/.fleet-manager/...) are consistent with a fleet router but are not surprising for this purpose.
Instruction Scope
SKILL.md stays within purpose: it instructs installing a fleet router (herd/herd-node), installing backends (DiffusionKit, mflux), and calling local HTTP endpoints for image generation/monitoring. It does not ask to read unrelated user data or external secrets. Note: the instructions require downloading model weights (HuggingFace) and running install/patch scripts—these are expected for model usage but involve substantial network I/O and running third‑party code.
Install Mechanism
The skill is instruction-only (no install spec). However, the guide tells users to run pip install ollama-herd and uv tool install diffusionkit, which will fetch and execute third‑party packages/binaries at install time. This is normal for such tooling but increases the attack surface compared to a purely local-only script; users should verify the provenance of those packages and scripts.
Credentials
The skill requests no environment variables or credentials. All runtime interactions are local (localhost) or involve downloading model weights from known model hosts (HuggingFace) as part of normal operation. There are no unrelated secret requests.
Persistence & Privilege
always:false and no special privileges requested. The skill does not instruct modifying other skills or system-wide configurations beyond installing tools for the router and node components; autonomous invocation is allowed but that is the platform default.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install stable-diffusion-sd3 - 安装完成后，直接呼叫该 Skill 的名称或使用
/stable-diffusion-sd3触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.2
Cross-platform support: macOS, Linux, and Windows. Updated OS metadata, descriptions, and hardware recommendations.
v1.0.1
- Expanded and clarified Stable Diffusion focus throughout documentation.
- Updated wording to explicitly mention "Stable Diffusion" and related model names in all sections, including setup, usage, and parameters.
- Added Chinese and Spanish phrases in description for broader accessibility.
- No functional or code changes — documentation only update.
v1.0.0
Initial release: Stable Diffusion 3 image generation on Apple Silicon with fully local control and device fleet management.
- Supports SD3 Medium (fast) and SD3.5 Large (highest quality) with MLX-native DiffusionKit backend.
- Integrates Flux models via mflux and Ollama native image generation.
- Local fleet routing with intelligent queue management and API/web dashboard monitoring.
- No reliance on cloud APIs or external model downloads during install—everything runs and stays on your hardware.
- Simple CLI and Python API for image generation and fleet/node management.
- Additional features: shared dashboard for images and LLMs, optional STT and embeddings via unified API.
元数据
常见问题
Stable Diffusion Sd3 是什么？
Stable Diffusion 3 and SD3.5 Large on Apple Silicon — generate Stable Diffusion images locally with DiffusionKit's MLX-native backend. SD3 Medium for fast St... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 211 次。
如何安装 Stable Diffusion Sd3？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install stable-diffusion-sd3」即可一键安装，无需额外配置。
Stable Diffusion Sd3 是免费的吗？
是的，Stable Diffusion Sd3 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Stable Diffusion Sd3 支持哪些平台？
Stable Diffusion Sd3 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（darwin）。
谁开发了 Stable Diffusion Sd3？
由 Twin Geeks（@twinsgeeks）开发并维护，当前版本 v1.0.2。
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