huggingface-lora-space-builder

Topics in the source

• Gradio LoRA Space Builder
• What "good" looks like for these demos
• Workflow
• Phase 1 — Gather LoRA info
• Phase 2 — Pick the base pipeline
• Phase 3 — Design the UI for this LoRA
• Phase 4 — Write the Space files
• app.py

Build and publish a Gradio demo on Hugging Face Spaces that runs inference with a user-provided LoRA. Use whenever someone asks to create, generate, ship, or publish "a Space", "a demo", "a Gradio app", or "a playground" for a LoRA — whether the base model is Qwen-Image, Qwen-Image-Edit, LTX, or another diffusion model. Also use when someone describes a LoRA they trained or hosts on the Hub and wants to share it. The default target is ZeroGPU hardware and the default inference library is diffusers when the base model supports it. The output is a real, published Space (private by default) that the user can try in the browser, not a local script. The demo should feel handcrafted for this specific LoRA, not a generic template with the LoRA bolted on. Two LoRAs that share a task can still need different demos: a pose-control video LoRA and an outpainting video LoRA both take video in and produce video out, but the inputs the user provides, the preprocessing, and the controls are completely different. Recognizing that is the central job here. Concretely, a good demo: Loads fast and runs fast — minimal model loading, sensible step count, no wasted computation per call. Has a UI with exac

This is an excerpt. Refer to the complete source and its current requirements.