Bernini Full Text to Video

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

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

◄promptA short smooth video of a red ceramic teapot rotating slowly on a white table.►

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

◄num_frames9►

◄fps16►

◄width512►

◄height512►

◄steps4►

◄seed3456►

◄quality_presetstandard►

◄accelerationwan2.2_lightx2v_4step►

◄memory_modekeep_loaded_batch►

CategoryRunningHub/Bernini

Inputs (11)

Name	Type	Default	Description
prompt	STRING	A short smooth video of a red ceramic teapot rotating slowly on a white table.	Text prompt or edit instruction.
negative_prompt	STRING	low quality, blurry, distorted, text, watermark	Negative prompt.
num_frames	INT	95–129	Number of output frames. Higher values increase VRAM use and runtime.
fps	INT	161–60	Frame rate written into the returned video.
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	34560–4294967295	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
video	VIDEO	—