Text-to-Video
Diffusers
English
anime
video-generation
diffusion-transformer
flow-matching
wan
commercial-use
quantized
fp8_scaled
fp8
int4_convrot
int4
convrot
Instructions to use siouni/AnimeGen-T2V-Quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use siouni/AnimeGen-T2V-Quantized with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("siouni/AnimeGen-T2V-Quantized", torch_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
AnimeGen-T2V-Quantized
このリポジトリは、元モデル aidealab/AnimeGen-T2V を複数形式へ量子化したモデルです。
Comfy-UIでの仕様を想定しています。
量子化情報
- 収録形式:
fp8_scaledint4_convrot
ライセンスその他はaidealab/AnimeGen-T2Vと同じです。
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