Instructions to use Cosmo-Hug/FeverDream with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Cosmo-Hug/FeverDream with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Cosmo-Hug/FeverDream", 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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# FeverDream
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It's trained at 576 resolution using the offset noise fix so generations are sharp and detailed with vibrant colors, deep blacks, and a well balanced contrast.
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This model was not trained with A.I. generated images or merged with any other models which means your images won't have that green/aqua color cast seen in so many models today.
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# FeverDream
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This is a fine tuning of SD1.5 and designed as a general purpose model trained on high quality photographs and traditional artworks upscaled and denoised before training to get the sharpest cleanest results possible.
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It's trained at 576 resolution using the offset noise fix so generations are sharp and detailed with vibrant colors, deep blacks, and a well balanced contrast.
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This model was not trained with A.I. generated images or merged with any other models which means your images won't have that green/aqua color cast seen in so many models today.
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