Instructions to use wikeeyang/Flux1-Dev-DedistilledMixTuned-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wikeeyang/Flux1-Dev-DedistilledMixTuned-v4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wikeeyang/Flux1-Dev-DedistilledMixTuned-v4", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
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# V4.0-Full Version:
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V4.0 模型,是在 V3.0 的基础上,融合了 SRPO 模型的写实与细腻,Krea 模型的艺术性与多风格,以及良好的质感与LoRA兼容性,模型的综合能力有较大提升。
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frameworks: PyTorch
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license: other
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# Flux1-Dev-DedistilledMixTuned V4.0 Full Version:
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V4.0 模型,是在 V3.0 的基础上,融合了 SRPO 模型的写实与细腻,Krea 模型的艺术性与多风格,以及良好的质感与LoRA兼容性,模型的综合能力有较大提升。
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