Realism - Engine
Collection
focused on realism
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4 items
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Updated
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10
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 | 30 & 4380 |
Epoch | 20 | Save Every N Epochs | 1 |
Comparison between the base model FLUX.1-dev and its adapter, a LoRA model tuned for super-realistic realism. [ 28 steps ]
However, it performs better in various aspects compared to its previous models, including face realism, ultra-realism, and others. previous versions [ 28 steps ]
Model Name | Description | Link |
---|---|---|
Canopus-LoRA-Flux-FaceRealism | LoRA model for Face Realism | Canopus-LoRA-Flux-FaceRealism |
Canopus-LoRA-Flux-UltraRealism-2.0 | LoRA model for Ultra Realism | Canopus-LoRA-Flux-UltraRealism-2.0 |
Flux.1-Dev-LoRA-HDR-Realism [Experimental Version] | LoRA model for HDR Realism | Flux.1-Dev-LoRA-HDR-Realism |
Flux-Realism-FineDetailed | Fine-detailed realism-focused model | Flux-Realism-FineDetailed |
Demo Name | Description | Link |
---|---|---|
FLUX-LoRA-DLC | Demo for FLUX LoRA DLC | FLUX-LoRA-DLC |
FLUX-REALISM | Demo for FLUX Realism | FLUX-REALISM |
Feature | Description |
---|---|
Labeling | florence2-en (natural language & English) |
Total Images Used for Training | 55 [Hi-Res] |
Best Dimensions | - 1024 x 1024 (Default) |
- 768 x 1024 |
Repository Link | Description |
---|---|
Flux-Super-Realism-LoRA | Flux Super Realism LoRA model repository for high-quality realism generation |
from gradio_client import Client
client = Client("prithivMLmods/FLUX-REALISM")
result = client.predict(
prompt="A tiny astronaut hatching from an egg on the moon, 4k, planet theme",
seed=0,
width=1024,
height=1024,
guidance_scale=6,
randomize_seed=True,
api_name="/run"
#takes minimum of 30 seconds
)
print(result)
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 = "strangerzonehf/Flux-Super-Realism-LoRA"
trigger_word = "Super Realism" #triggerword
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words: You should use
Super Realism
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