---
license: other
license_name: bespoke-lora-trained-license
license_link: https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- character
- futurama
- brain slug
- brainslug
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: brain slug
widget:
- text: 'A photo of a confused ginger woman staring blankly in the air with a (brain slug) made of green jelly (attached to her head), Very detailed, clean, high quality, sharp image'
output:
url: >-
26038803.jpeg
- text: 'The girl with a brain slug earring'
output:
url: >-
26039878.jpeg
- text: 'A photo of a shocked old granny with a gooey brain slug attached to her head'
output:
url: >-
26038804.jpeg
- text: 'A photo of a brain slug enjoying a sunny day at the beach'
output:
url: >-
26037906.jpeg
---
# Brain Slug [FLUX]
A failed-ish attempt to recreate my SD brain-slug LoRA.
### ⚠️ Seems like LoRA weight strength of at least 1.5 is needed to generate the intended Brain-Slug ⚠️"Brain Slugs are a species of space parasite that attaches its jelly-like body to a victim's head and takes control of their brain. The specimen is lime in color and consists of a translucent jelly-like body complete with two feelers and one large eyeball. An adult brain slug is about the size of a fist."
I have made the training dataset available on Huggingface
## Download model Weights for this model are available in Safetensors format. [Download](/Norod78/brain-slug-flux/tree/main) them in the Files & versions tab. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('Norod78/brain-slug-flux', weight_name='Brain_Slug_FLUX.safetensors') image = pipeline('Your custom prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)