How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
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("oyvsar/mlvn")

prompt = "MLVN"
image = pipe(prompt).images[0]

Mlvn

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train

This is just a model to learn how training a model works, to see what possibilities I have. It is trained on different logos of a pub,

and also images inside and outside of the pub, as well as advertisement and SoMe-posters from the pub.

Trigger words

You should use MLVN 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('oyvsar/mlvn', 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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