Instructions to use agmjd/cipher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use agmjd/cipher 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("agmjd/cipher") prompt = "Rappa/(star_rail/),masterpiece,best quality,Rappa/(star_rail/),solo,green eyes,navel,pink hair,horns,hat,baseball cap,short hair,multicolored hair,breasts,ahoge,oni horns,black headwear,thighs,highleg,bikini,, Negative prompt: ng_deepnegative_v1_75t,(badhandv4:1.2),EasyNegative,(worst quality:2),,nsfw, Steps: 20, Sampler: Euler a, CFG scale: 7.0, Seed: 1947776853, Size: 1024x1024, Model hash: befc694a29, Model: WAI_NSFW-illustrious-SDXL_v15.safetensors, Denoising strength: 0, RNG: CPU, Lora 1: Rappa_XL å´©åæç©¹éé ä¹±ç ´, Lora Hash 1: 8374bed1eb, Lora Weight 1: 0.8, vae_name: automatic" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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Browse files
images/eb43ccb66d3aed5fc623be81e1456b2e9eef9c41edd0a81072a9ea73edad8227.png
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