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cerspense
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zeroscope_v1_320s

Diffusers
TextToVideoSDPipeline
Text-to-Video
Model card Files
xet
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1
How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v1_320s", dtype=torch.bfloat16, device_map="cuda")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]

Modelscope without the watermark, trained in 320x320 from the original weights, with no skipped frames for less flicker. See comparison here: https://www.youtube.com/watch?v=r4tOc30Zu0w Model was trained on a subset of the vimeo90k dataset + a selection of music videos

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