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
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Download PUBLISH_CHECKLIST.md from YunusTAS13/InkNoir-Core: direct link, hf CLI and curl.
- Browser
- Download file 845 Bytes
-
https://huggingface.co/YunusTAS13/InkNoir-Core/resolve/main/PUBLISH_CHECKLIST.md
- Command line
-
hf download hf://YunusTAS13/InkNoir-Core/PUBLISH_CHECKLIST.md
-
curl -L -o PUBLISH_CHECKLIST.md https://huggingface.co/YunusTAS13/InkNoir-Core/resolve/main/PUBLISH_CHECKLIST.md
845 Bytes
InkNoir Core full release checklist
- Complete Diffusers pipeline included at repository root.
- Standalone half-precision
InkNoir_Core_Full.safetensorsincluded. - Optional unfused adapter included under
adapters/. - Full pipeline loaded locally without a LoRA and generated a smoke-test image.
- No
lora_*keys remain in the fused UNet or single-file checkpoint. - Beginner launcher
run_inknoir.pyincluded. -
requirements.txtincluded. - English/Turkish setup and usage instructions included.
- Main gallery, prompt catalog, independent benchmark and prompt-control tests included.
- 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.