Cossale/Frames2-Flex.1

backdrops_v2

Model trained with AI Toolkit by Ostris

Prompt

FRM$ a majestic mountain range with snow-capped peaks in the background, illuminated by the setting sun. The sky is a beautiful mix of oranges, pinks, and purples, creating a stunning backdrop for the majestic peaks.

Prompt

FRM$ a river flowing near a mountain and plains land, firewatch style, watch tower on mountain, purplish dominant color, animals

Prompt

FRM$ a breathtaking view of the Great Smoky Mountains from the top of a mountain at sunset. The sky is a beautiful mix of oranges, pinks, and purples, and the clouds are illuminated by the setting sun. The mountains are silhouetted against the sky, creating a stunning landscape.

Prompt

FRM$ a small, secluded lake nestled amidst a valley of stylized, low-poly mountains, reminiscent of the Firewatch art style. A simple wooden watchtower overlooks the lake, its silhouette sharp against the warm, orange and pink hues of a sunset sky. A small herd of deer graze peacefully near the lakeshore. The overall scene should evoke a sense of tranquility and isolation, with a vibrant yet slightly muted color palette.

Trigger words

No trigger words defined.

Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('ostris/Flex.1-alpha', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('Cossale/Frames-Flex2', weight_name='backdrops_v2.safetensors')
image = pipeline('FRM$ a majestic mountain range with snow-capped peaks in the background, illuminated by the setting sun. The sky is a beautiful mix of oranges, pinks, and purples, creating a stunning backdrop for the majestic peaks.').images[0]
image.save("my_image.png")

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers