Instructions to use Muapi/karinami-inkblush-mode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/karinami-inkblush-mode with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/karinami-inkblush-mode") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Muapi/karinami-inkblush-mode: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/Muapi/karinami-inkblush-mode/resolve/main/README.md
- Command line
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hf download hf://Muapi/karinami-inkblush-mode/README.md
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curl -L -o README.md https://huggingface.co/Muapi/karinami-inkblush-mode/resolve/main/README.md
1 kB
| license: openrail++ | |
| library_name: diffusers | |
| base_model: black-forest-labs/FLUX.1-dev | |
| tags: | |
| - lora | |
| - text-to-image | |
| - stable-diffusion | |
| - flux | |
| - flux.1-d | |
| pipeline_tag: text-to-image | |
| # Karinami Inkblush mode | |
|  | |
| **Base model**: Flux.1 D | |
| **Trained words**: Karinami Inkblush mode, thick ink outlines, soft marker gradients, era 2020s indie illustration, Inkblush style, sketchbook paper filter | |
| ## 🧠 Usage (Python) | |
| 🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys) | |
| ```python | |
| import requests, os | |
| url = "https://api.muapi.ai/api/v1/flux_dev_lora_image" | |
| headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")} | |
| payload = { | |
| "prompt": "masterpiece, best quality, 1girl, looking at viewer", | |
| "model_id": [{"model": "civitai:1426853@1634287", "weight": 1.0}], | |
| "width": 1024, | |
| "height": 1024, | |
| "num_images": 1 | |
| } | |
| print(requests.post(url, headers=headers, json=payload).json()) | |
| ``` | |