Bernini Full Text to Image

Full Bernini text-to-image using Bernini-Diffusers only.

By RH-RunningHub·Created 2 months ago·Updated 2 months ago· 7

◄promptA clean studio product image of a red ceramic teapot on a white table, soft daylight►

◄negative_promptlow quality, blurry, distorted, text, watermark►

◄width512►

◄height512►

◄steps4►

◄seed1234►

◄quality_presetstandard►

◄accelerationwan2.2_lightx2v_4step►

◄memory_modekeep_loaded_batch►

CategoryRunningHub/Bernini

Inputs (9)

Name	Type	Default	Description
prompt	STRING	A clean studio product image of a red ceramic teapot on a white table, soft daylight	Text prompt or edit instruction.
negative_prompt	STRING	low quality, blurry, distorted, text, watermark	Negative prompt.
width	INT	51264–2048	Output width in pixels. Larger values increase VRAM use and runtime.
height	INT	51264–2048	Output height in pixels. Larger values increase VRAM use and runtime.
steps	INT	41–100	Diffusion steps.
seed	INT	12340–4294967295	Random seed. Values are clamped to NumPy's valid 0 to 2**32-1 range before inference.
quality_preset	COMBO	standard	standard balances speed and quality; quality spends more planning time for better output.
acceleration	COMBO	wan2.2_lightx2v_4step	Auto-load the Wan2.2 T2V LightX2V 4-step LoRA pair from ComfyUI/models/loras when available.
memory_mode	COMBO	keep_loaded_batch	keep_loaded_batch keeps the Bernini pipeline cached for faster consecutive jobs; low_vram_unload frees memory after each run.

Name	Type	Description
image	IMAGE	—