Instructions to use Bl4ckSpaces/SpacesFusion_V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Bl4ckSpaces/SpacesFusion_V3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Bl4ckSpaces/SpacesFusion_V3", 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
SpacesFusion_V3 (Final)
The perfected iteration. Built upon the solid anatomical foundation of SpacesFusion_V1, using High-Precision FP32 TIES-Merging to surgically inject missing capabilities.
The Architecture
- Base:
SpacesFusion_V1(Ensures Anatomical Stability & Support for 1536px). - Knowledge Delta: Derived from
IllumiYume(Weight: 1.1). Corrects the "Knowledge Gap" for 2025 datasets (e.g., Marvel Rivals, newer anime). - Style Delta: Derived from
NoobAI XL(Weight: 0.8). Enhances line sharpness and shading depth.
TIES-Merging Configuration
- Precision: FP32 Calculation -> FP16 Storage.
- Density: 0.5 (Noise Pruning).
- Conflict Resolution: Enabled (Prevents Knowledge/Style clashes).
Recommended Settings
- V-Prediction: Enabled (Mandatory).
- CFG: 5.0 - 7.0
- Sampler: Euler a / DPM++ 2M SDE.
- Downloads last month
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Model tree for Bl4ckSpaces/SpacesFusion_V3
Base model
Bl4ckSpaces/SpacesFusion_V1