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("uwcc/casualpolarbear")
prompt = "A church in a field on a sunny day, [trigger] style."
image = pipe(prompt).images[0]casualpolarbear
Model trained with AI Toolkit by Ostris
- Prompt
- A church in a field on a sunny day, [trigger] style.
- Prompt
- A seal plays with a ball on the beach, [trigger] style.
- Prompt
- A clown at the circus rides on a zebra, [trigger] style.
- Prompt
- [trigger]
Trigger words
You should use CASUALPOLARBEAR to trigger the image generation.
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('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('uwcc/casualpolarbear', weight_name='casualpolarbear')
image = pipeline('A church in a field on a sunny day, [trigger] style.').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for uwcc/casualpolarbear
Base model
black-forest-labs/FLUX.1-dev