---
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
- puppet
- cactus
- kishkashta
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: green monster
widget:
- text: A green monster in a leather jacket riding a motorcycle in the desert
output:
url: 29675012.jpeg
- text: >-
A green monster is a DJ at a night club, fish eye lens, smoke machine, lazer
lights, holding a martini
output:
url: 29675017.jpeg
- text: >-
A green monster with a red wig, playing chess at the park, bomb going off in
the background
output:
url: 29675019.jpeg
- text: green monster eating spaghetti
output:
url: 29675022.jpeg
- text: >-
green monster is smoking a Marijuana joint next to a Marijuana plant in a
pot
output:
url: 29675027.jpeg
datasets:
- Norod78/KishKashta
---
# Green Cactus Monster (KishKashta) [FLUX]
Kishkashta is a very niche character
Use "green monster" in your prompts to trigger the generation
Lora trained with Astria.AI
Also available on CivitAI
## Trigger words You should use `green monster` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/Norod78/green-cactus-monster-kishkashta-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 device = "cuda" if torch.cuda.is_available() else "cpu" pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device) pipeline.load_lora_weights('Norod78/green-cactus-monster-kishkashta-flux', weight_name='Flux-Green_Monster-KishKashta-LoRA-1611173.safetensors') image = pipeline('A green monster is eating spaghetti').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)