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("jakedahn/flux-midsummer-blues")
prompt = "funny cat holding a sign \"I <3 REPLICATE\", dark blue scene, illustrated MSMRB style"
image = pipe(prompt).images[0]Flux Midsummer Blues
- Prompt
- funny cat holding a sign "I <3 REPLICATE", dark blue scene, illustrated MSMRB style
- Prompt
- a cat licking a large felt ball with a drawing of the Golden Gate Bridge on it, illustrated MSMRB style
- Prompt
- funny white cat holding a sign "I <3 REPLICATE", sketch, grainy storybook illustration, black and white, illustrated MSMRB style
- Prompt
- cat with a hat, illustrated MSMRB style
- Prompt
- man wearing a suit, illustrated MSMRB style
- Prompt
- san francisco, illustrated MSMRB style
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
Trigger words
You should use MSMRB to trigger the image generation.
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.float16).to('cuda')
pipeline.load_lora_weights('jakedahn/flux-midsummer-blues', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for jakedahn/flux-midsummer-blues
Base model
black-forest-labs/FLUX.1-dev