Instructions to use TheRemixer/misc-small-experiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheRemixer/misc-small-experiment with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CabalResearch/NoobAI-Flux2VAE-RectifiedFlow-0.3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("TheRemixer/misc-small-experiment") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
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## **Loras/Mugen-Consistency-Test-Muon-000004.safetensors**
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Consistency lora trained similarly to the ones below, but with Muon
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## **Loras/Mugen-lanzcos-test-000001.safetensors**
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Very small lora trained after replacing the downscaling algorithm used in sd-scripts from `cv2.INTER_AREA` to `cv2.INTER_LANCZOS4`
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Works to increase sharpness and fine details when setting the positive conditioning's original size greater than the target size's.
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- ComfyUI nodes to make this easier [HERE](https://github.com/lRemixl/ComfyUI-sdxl-micro-conditioning)
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My reasoning for this is in this [.docx file](Loras/documents/Reasoning%20behind%20lanzcos%20downscaling.docx)
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## **Loras/Mugen-Consistency-Test-Muon-000004.safetensors**
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Consistency lora trained similarly to the ones below, but with Muon
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