Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-1-5
dark-anime
image-to-image
turkish-prompts
Instructions to use YunusTAS13/InkNoir-Core with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YunusTAS13/InkNoir-Core with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YunusTAS13/InkNoir-Core", 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
File size: 845 Bytes
9d5c45f d88e593 9d5c45f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # InkNoir Core full release checklist
- [x] Complete Diffusers pipeline included at repository root.
- [x] Standalone half-precision `InkNoir_Core_Full.safetensors` included.
- [x] Optional unfused adapter included under `adapters/`.
- [x] Full pipeline loaded locally without a LoRA and generated a smoke-test image.
- [x] No `lora_*` keys remain in the fused UNet or single-file checkpoint.
- [x] Beginner launcher `run_inknoir.py` included.
- [x] `requirements.txt` included.
- [x] English/Turkish setup and usage instructions included.
- [x] Main gallery, prompt catalog, independent benchmark and prompt-control tests included.
- [x] DreamShaper 8 is attributed as the base model and CreativeML Open RAIL-M is identified.
- [ ] Publisher must verify training-image redistribution rights before claiming a fully cleared dataset provenance.
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