Flux LoRA Collections
Collection
Flux THE LoRA • 131 items • Updated • 33
How to use prithivMLmods/Flux.1-Dev-Movie-Boards-LoRA with Diffusers:
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("prithivMLmods/Flux.1-Dev-Movie-Boards-LoRA")
prompt = "movieboard, A black and white photograph of a man in a space suit is seen on a page of a magazine. The man is wearing a white helmet on his head, and is standing in a field of tall grass. The background of the photograph is a bright yellow circle, and the word \"InterSTAR\" is written in bold black letters at the top of the page. The number \"20\" is in the upper right corner of the frame."
image = pipe(prompt).images[0]



The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
prithivMLmods/Flux.1-Dev-Movie-Boards-LoRA
Image Processing Parameters
| Parameter | Value | Parameter | Value |
|---|---|---|---|
| LR Scheduler | constant | Noise Offset | 0.03 |
| Optimizer | AdamW | Multires Noise Discount | 0.1 |
| Network Dim | 64 | Multires Noise Iterations | 10 |
| Network Alpha | 32 | Repeat & Steps | 16 & 2100 |
| Epoch | 14 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 11
import torch
from pipelines import DiffusionPipeline
base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Flux.1-Dev-Movie-Boards-LoRA"
trigger_word = "movieboard"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use movieboard to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Base model
black-forest-labs/FLUX.1-dev