Add LoRA space builder skill

.claude-plugin/marketplace.json

@@ -5,7 +5,7 @@
   },
   "metadata": {
     "description": "Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub",
-    "version": "1.0.4"
+    "version": "1.0.5"
   },
   "plugins": [
     {
@@ -97,6 +97,12 @@
       "source": "./skills/huggingface-zerogpu",
       "skills": "./",
       "description": "Coding rules for Gradio Spaces using Hugging Face Spaces ZeroGPU hardware. Covers `@spaces.GPU`, duration and quota tuning, pickle-based process isolation, `gr.State` semantics across the worker boundary, the CUDA availability model, concurrency safety, and CUDA wheel-only build constraints."
+    },
+    {
+      "name": "huggingface-lora-space-builder",
+      "source": "./skills/huggingface-lora-space-builder",
+      "skills": "./",
+      "description": "Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default."
     }
   ]
 }

.claude-plugin/plugin.json

@@ -1,7 +1,7 @@
 {
   "name": "huggingface-skills",
   "description": "Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub",
-  "version": "1.0.4",
+  "version": "1.0.5",
   "author": {
     "name": "Hugging Face"
   },

.cursor-plugin/marketplace.json

@@ -5,7 +5,7 @@
   },
   "metadata": {
     "description": "Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub",
-    "version": "1.0.4"
+    "version": "1.0.5"
   },
   "plugins": [
     {

.cursor-plugin/plugin.json

@@ -3,7 +3,7 @@
   "skills": "skills",
   "mcpServers": ".mcp.json",
   "description": "Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub",
-  "version": "1.0.4",
+  "version": "1.0.5",
   "author": {
     "name": "Hugging Face"
   },

README.md

@@ -100,6 +100,7 @@ This repository contains a few skills to get you started. You can also contribut
 | `huggingface-gradio` | Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots. | [SKILL.md](skills/huggingface-gradio/SKILL.md) |
 | `huggingface-llm-trainer` | Train or fine-tune language models using TRL on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes hardware selection, cost estimation, Trackio monitoring, and Hub persistence. | [SKILL.md](skills/huggingface-llm-trainer/SKILL.md) |
 | `huggingface-local-models` | Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving. | [SKILL.md](skills/huggingface-local-models/SKILL.md) |
+| `huggingface-lora-space-builder` | Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default. | [SKILL.md](skills/huggingface-lora-space-builder/SKILL.md) |
 | `huggingface-paper-publisher` | Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles. | [SKILL.md](skills/huggingface-paper-publisher/SKILL.md) |
 | `huggingface-papers` | Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata like authors, linked models, datasets, Spaces, and media URLs when needed. | [SKILL.md](skills/huggingface-papers/SKILL.md) |
 | `huggingface-tool-builder` | Build reusable scripts for Hugging Face Hub and API workflows. Useful for chaining API calls, enriching Hub metadata, or automating repeated tasks. | [SKILL.md](skills/huggingface-tool-builder/SKILL.md) |

agents/AGENTS.md

@@ -10,6 +10,7 @@ These skills are:
  - huggingface-gradio -> "skills/huggingface-gradio/SKILL.md"
  - huggingface-llm-trainer -> "skills/huggingface-llm-trainer/SKILL.md"
  - huggingface-local-models -> "skills/huggingface-local-models/SKILL.md"
+ - huggingface-lora-space-builder -> "skills/huggingface-lora-space-builder/SKILL.md"
  - huggingface-paper-publisher -> "skills/huggingface-paper-publisher/SKILL.md"
  - huggingface-papers -> "skills/huggingface-papers/SKILL.md"
  - huggingface-tool-builder -> "skills/huggingface-tool-builder/SKILL.md"
@@ -30,6 +31,7 @@ huggingface-datasets: `Use this skill for Hugging Face Dataset Viewer API workfl
 huggingface-gradio: `Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.`
 huggingface-llm-trainer: `Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.`
 huggingface-local-models: `"Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving."`
+huggingface-lora-space-builder: `Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.`
 huggingface-paper-publisher: `Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.`
 huggingface-papers: `Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.`
 huggingface-tool-builder: `Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.`

gemini-extension.json

@@ -1,7 +1,7 @@
 {
   "name": "huggingface-skills",
   "description": "Provides access to the Hugging Face Skills.",
-  "version": "1.0.4",
+  "version": "1.0.5",
   "contextFileName": "agents/AGENTS.md",
   "mcpServers": {
     "huggingface-skills": {