Text-to-Video
Diffusers
English
video-generation
diffusion
autoregressive
long-horizon
long-video
fixed-camera
steady-forcing
nature-flow
static-view
spatial-persistence
motion-continuity
nature-video
fluid-dynamics
background-anchoring
temporal-consistency
dual-memory
wan2.1
reward-forcing
arxiv:2606.7661673
Eval Results (legacy)
Instructions to use minar09/Steady-Forcing-T2V-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use minar09/Steady-Forcing-T2V-1.3B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("minar09/Steady-Forcing-T2V-1.3B", dtype=torch.bfloat16, device_map="cuda") prompt = "A beautiful South Korean empty sea beach scene recorded by a completely fixed, static, tripod mounted camera. The camera is not seen, it does not move, tilt, pan, or zoom at any point. The sandy shoreline stretches across the frame, with gentle waves rolling in from the horizon and softly breaking against the beach in a continuous rhythm. The motion of the tides is natural and consistent, creating subtle ripples and foamy edges as the water meets the sand. The beach itself remains perfectly static, with smooth sand, scattered shells, and distant rocks unmoving in the background. The atmosphere is stunning, as the sun hangs low near the horizon, casting warm golden and orange tones across the sky and reflecting softly on the water's surface. The distant sea remains calm, with no flicker, jumps, resets, or artificial distortions, while the tide flows seamlessly in one constant direction. The scene unfolds in real time over a long duration, emphasizing the physical dynamics of the ocean waves and the tranquil beauty of the sunset. The video maintains temporal continuity across all frames, showing the uninterrupted progression of tides softly hitting the sandy beach without cinematic exaggeration or dramatic effects. [60s]" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle