Instructions to use AiAF/Diffusers_bigLust_v17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AiAF/Diffusers_bigLust_v17 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AiAF/Diffusers_bigLust_v17", 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
Commit History
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redid conversion with --half flag and --to_safetensors flag to export weights in safetensors format in fp16 format to save storage space and vram for training (it exportrd weights in FP32 by defaut so the resulting files were ~13.9 GB in combined size)
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Diffusers formay version of BigLust 1.7 ( https://civitai.com/models/1433766/biglust-17 )
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