Instructions to use jeron/me with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jeron/me 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("jeron/me") prompt = "UNICODE\u0000\u0000J\u0000e\u0000r\u0000o\u0000n\u0000 \u0000i\u0000s\u0000 \u0000s\u0000t\u0000a\u0000n\u0000d\u0000i\u0000n\u0000g\u0000 \u0000i\u0000n\u0000s\u0000i\u0000d\u0000e\u0000 \u0000a\u0000 \u0000c\u0000o\u0000z\u0000y\u0000,\u0000 \u0000m\u0000o\u0000d\u0000e\u0000r\u0000n\u0000 \u0000b\u0000o\u0000a\u0000t\u0000.\u0000 \u0000H\u0000e\u0000 \u0000h\u0000a\u0000s\u0000 \u0000s\u0000h\u0000o\u0000r\u0000t\u0000 \u0000b\u0000l\u0000a\u0000c\u0000k\u0000 \u0000h\u0000a\u0000i\u0000r\u0000 \u0000a\u0000n\u0000d\u0000 \u0000a\u0000 \u0000m\u0000u\u0000s\u0000c\u0000u\u0000l\u0000a\u0000r\u0000 \u0000p\u0000h\u0000y\u0000s\u0000i\u0000q\u0000u\u0000e\u0000.\u0000 \u0000H\u0000e\u0000 \u0000i\u0000s\u0000 \u0000d\u0000r\u0000e\u0000s\u0000s\u0000e\u0000d\u0000 \u0000i\u0000n\u0000 \u0000a\u0000 \u0000c\u0000a\u0000s\u0000u\u0000a\u0000l\u0000 \u0000y\u0000e\u0000t\u0000 \u0000s\u0000t\u0000y\u0000l\u0000i\u0000s\u0000h\u0000 \u0000o\u0000u\u0000t\u0000f\u0000i\u0000t\u0000:\u0000 \u0000a\u0000 \u0000b\u0000e\u0000i\u0000g\u0000e\u0000 \u0000l\u0000e\u0000a\u0000t\u0000h\u0000e\u0000r\u0000 \u0000j\u0000a\u0000c\u0000k\u0000e\u0000t\u0000,\u0000 \u0000a\u0000 \u0000d\u0000a\u0000r\u0000k\u0000 \u0000b\u0000r\u0000o\u0000w\u0000n\u0000 \u0000p\u0000o\u0000l\u0000o\u0000 \u0000s\u0000h\u0000i\u0000r\u0000t\u0000,\u0000 \u0000a\u0000n\u0000d\u0000 \u0000w\u0000h\u0000i\u0000t\u0000e\u0000 \u0000t\u0000r\u0000o\u0000u\u0000s\u0000e\u0000r\u0000s\u0000.\u0000 \u0000H\u0000i\u0000s\u0000 \u0000j\u0000a\u0000c\u0000k\u0000e\u0000t\u0000 \u0000i\u0000s\u0000 \u0000u\u0000n\u0000b\u0000u\u0000t\u0000t\u0000o\u0000n\u0000e\u0000d\u0000,\u0000 \u0000r\u0000e\u0000v\u0000e\u0000a\u0000l\u0000i\u0000n\u0000g\u0000 \u0000t\u0000h\u0000e\u0000 \u0000p\u0000o\u0000l\u0000o\u0000 \u0000s\u0000h\u0000i\u0000r\u0000t\u0000 \u0000u\u0000n\u0000d\u0000e\u0000r\u0000n\u0000e\u0000a\u0000t\u0000h\u0000.\u0000 \u0000H\u0000i\u0000s\u0000 \u0000h\u0000a\u0000n\u0000d\u0000s\u0000 \u0000a\u0000r\u0000e\u0000 \u0000r\u0000e\u0000s\u0000t\u0000i\u0000n\u0000g\u0000 \u0000o\u0000n\u0000 \u0000t\u0000h\u0000e\u0000 \u0000w\u0000i\u0000n\u0000d\u0000o\u0000w\u0000 \u0000f\u0000r\u0000a\u0000m\u0000e\u0000 \u0000w\u0000h\u0000i\u0000c\u0000h\u0000 \u0000h\u0000e\u0000 \u0000i\u0000s\u0000 \u0000l\u0000e\u0000a\u0000n\u0000i\u0000n\u0000g\u0000 \u0000a\u0000g\u0000a\u0000i\u0000n\u0000s\u0000t\u0000,\u0000 \u0000a\u0000n\u0000d\u0000 \u0000h\u0000e\u0000 \u0000i\u0000s\u0000 \u0000l\u0000o\u0000o\u0000k\u0000i\u0000n\u0000g\u0000 \u0000l\u0000e\u0000f\u0000t\u0000 \u0000o\u0000f\u0000 \u0000t\u0000h\u0000e\u0000 \u0000c\u0000a\u0000m\u0000e\u0000r\u0000a\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000a\u0000 \u0000c\u0000o\u0000n\u0000t\u0000e\u0000m\u0000p\u0000l\u0000a\u0000t\u0000i\u0000v\u0000e\u0000 \u0000e\u0000x\u0000p\u0000r\u0000e\u0000s\u0000s\u0000i\u0000o\u0000n\u0000.\u0000 \u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - lora | |
| - diffusers | |
| - template:sd-lora | |
| widget: | |
| - text: "UNICODE\0\0J\0e\0r\0o\0n\0 \0i\0s\0 \0s\0t\0a\0n\0d\0i\0n\0g\0 \0i\0n\0s\0i\0d\0e\0 \0a\0 \0c\0o\0z\0y\0,\0 \0m\0o\0d\0e\0r\0n\0 \0b\0o\0a\0t\0.\0 \0H\0e\0 \0h\0a\0s\0 \0s\0h\0o\0r\0t\0 \0b\0l\0a\0c\0k\0 \0h\0a\0i\0r\0 \0a\0n\0d\0 \0a\0 \0m\0u\0s\0c\0u\0l\0a\0r\0 \0p\0h\0y\0s\0i\0q\0u\0e\0.\0 \0H\0e\0 \0i\0s\0 \0d\0r\0e\0s\0s\0e\0d\0 \0i\0n\0 \0a\0 \0c\0a\0s\0u\0a\0l\0 \0y\0e\0t\0 \0s\0t\0y\0l\0i\0s\0h\0 \0o\0u\0t\0f\0i\0t\0:\0 \0a\0 \0b\0e\0i\0g\0e\0 \0l\0e\0a\0t\0h\0e\0r\0 \0j\0a\0c\0k\0e\0t\0,\0 \0a\0 \0d\0a\0r\0k\0 \0b\0r\0o\0w\0n\0 \0p\0o\0l\0o\0 \0s\0h\0i\0r\0t\0,\0 \0a\0n\0d\0 \0w\0h\0i\0t\0e\0 \0t\0r\0o\0u\0s\0e\0r\0s\0.\0 \0H\0i\0s\0 \0j\0a\0c\0k\0e\0t\0 \0i\0s\0 \0u\0n\0b\0u\0t\0t\0o\0n\0e\0d\0,\0 \0r\0e\0v\0e\0a\0l\0i\0n\0g\0 \0t\0h\0e\0 \0p\0o\0l\0o\0 \0s\0h\0i\0r\0t\0 \0u\0n\0d\0e\0r\0n\0e\0a\0t\0h\0.\0 \0H\0i\0s\0 \0h\0a\0n\0d\0s\0 \0a\0r\0e\0 \0r\0e\0s\0t\0i\0n\0g\0 \0o\0n\0 \0t\0h\0e\0 \0w\0i\0n\0d\0o\0w\0 \0f\0r\0a\0m\0e\0 \0w\0h\0i\0c\0h\0 \0h\0e\0 \0i\0s\0 \0l\0e\0a\0n\0i\0n\0g\0 \0a\0g\0a\0i\0n\0s\0t\0,\0 \0a\0n\0d\0 \0h\0e\0 \0i\0s\0 \0l\0o\0o\0k\0i\0n\0g\0 \0l\0e\0f\0t\0 \0o\0f\0 \0t\0h\0e\0 \0c\0a\0m\0e\0r\0a\0 \0w\0i\0t\0h\0 \0a\0 \0c\0o\0n\0t\0e\0m\0p\0l\0a\0t\0i\0v\0e\0 \0e\0x\0p\0r\0e\0s\0s\0i\0o\0n\0.\0 \0" | |
| output: | |
| url: images/CHVG6XCKTTDV6SB6KAJBD39HD0.jpg | |
| base_model: black-forest-labs/FLUX.1-dev | |
| instance_prompt: jeron | |
| # me | |
| <Gallery /> | |
| ## Model description | |
| literally a lora of me lmfao | |
| ## Trigger words | |
| You should use `jeron` to trigger the image generation. | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/jeron/me/tree/main) them in the Files & versions tab. | |