--- 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] ## Model description

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)