Canopus-LoRA-Flux-UltraRealism-2.0

Prompt
woman in a red jacket, snowy, in the style of hyper-realistic portraiture, caninecore, mountainous vistas, timeless beauty, palewave, iconic, distinctive noses --ar 72:101 --stylize 750 --v 6

The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.

Model description

prithivMLmods/Canopus-LoRA-Flux-FaceRealism

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 & 3.8K+
Epoch 20 Save Every N Epochs 1
Labeling: florence2-en(natural language & English)

Total Images Used for Training : 70 [ Hi-RES ] & More ...............

Trigger words

You should use Ultra realistic to trigger the image generation.

Other Versions

Here’s a table format for the Hugging Face model "prithivMLmods/Canopus-LoRA-Flux-FaceRealism":

Attribute Details
Model Name Canopus-LoRA-Flux-FaceRealism
Model ID prithivMLmods/Canopus-LoRA-Flux-FaceRealism
Hugging Face URL Canopus-LoRA-Flux-FaceRealism
Model Type LoRA (Low-Rank Adaptation)
Primary Use Case Face Realism image generation
Supported Framework Hugging Face Diffusers
Data Type bfloat16, fp16, float32
Compatible Models Stable Diffusion, Flux models
Model Author prithivMLmods
LoRA Technique LoRA for image style transfer with a focus on generating realistic faces
Model Version Latest
License Open-Access
Tags LoRA, Face Realism, Flux, Image Generation

Setting Up

import torch
from pipelines import DiffusionPipeline

base_model = "prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "prithivMLmods/Canopus-LoRA-Flux-FaceRealism"
trigger_word = "Ultra realistic"  # Leave trigger_word blank if not used.
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

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