Text-to-Video
Diffusers
Safetensors
world-model
video-generation
image-to-video
interactive
camera-control
distillation
Instructions to use AlayaLab/Evoke-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlayaLab/Evoke-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AlayaLab/Evoke-Turbo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
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Use the original Alaya-EVOKE paper title in model card heading
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Use Alaya-EVOKE-Turbo title and simplify header badges
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Polish model card badges, highlight WBench best scores and simplify Turbo layout
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Release Evoke-Turbo merged FP32 checkpoint and model card
Verified signaturePublish the reviewed checkpoint-800 merged transformer at the repository root, preserving original FP32 weights. Include Evoke-compatible usage, WBench results, license and citation.479a3a1 -
initial commit
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