Instructions to use Keltezaa/CIM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Keltezaa/CIM 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("Keltezaa/CIM") prompt = "cum in mouth" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example
#1
by Keltezaa - opened
- README.md +4 -0
- images/example_0r9ptvqji.png +3 -0
README.md
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- text: '-'
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output:
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url: images/custom.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: cum in mouth
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license: cc-by-nc-nd-4.0
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---
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# CIM
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- text: '-'
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output:
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url: images/custom.png
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- text: cum in mouth
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output:
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url: images/example_0r9ptvqji.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: cum in mouth
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license: cc-by-nc-nd-4.0
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---
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# CIM
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images/example_0r9ptvqji.png
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Git LFS Details
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