metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
- flux-dev
- ultra
- realism
- photorealism
- hi-res
- face
- diffusion
widget:
- text: >-
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
output:
url: images/3.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Ultra realistic
license: creativeml-openrail-m
Canopus-LoRA-Flux-UltraRealism-2.0
The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
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.