Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Ciro_Negrogni
MagicArt35
Instructions to use Yntec/Trending with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Trending with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/Trending", 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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https://civitai.com/models/98543 (Photographic Trend)
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https://civitai.com/models/94687/photo-movie-x (AmovieX)
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https://civitai.com/models/98543 (Photographic Trend)
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https://civitai.com/models/94687/photo-movie-x (AmovieX)
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# Recipe
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- Merge Photographic Trend LoRA to checkpoint 1.0
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Model A:
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AmovieX
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OutPut:
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PhotographicTrendAmovieX
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- SuperMerger Weight sum Train Difference use MBW 0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1
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Model A:
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PhotographicTrendAmovieX
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Model B:
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AmovieX
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OutPut:
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Trending
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