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| 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 | 28 & 3400 |
| Epoch | 15 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 27 Flux-Super-Realism-LoRA model on Hugging Face:| Feature | Details |
|---|---|
| Model Name | Flux-Super-Realism-LoRA |
| Repository | strangerzonehf/Flux-Super-Realism-LoRA |
| Author | strangerzonehf |
| Description | Super-realism LoRA model designed to produce high-quality, hyper-realistic images using LoRA fine-tuning techniques. This model can generate lifelike textures, lighting, and intricate details. |
| Model Type | LoRA (Low-Rank Adaptation for Transformers) |
| Use Cases | - Photorealistic image generation - High-fidelity art - Texture detailing and enhancement |
| Primary Language | Not applicable (model is image-based) |
| Base Model | Model used as the foundation for LoRA fine-tuning (may vary per implementation) |
| License | Refer to Hugging Face model page for specific licensing information. |
| Tags | super-realism, LoRA, high-fidelity, hyper-realistic |
| Usage | This model is typically used with tools like Hugging Face's Diffusers or other libraries supporting LoRA fine-tuning for enhanced realism in image generation. |
| Pipeline | Use in StableDiffusionPipeline or compatible image generation pipelines. |
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-Realism-FineDetailed"
trigger_word = "Fine Detailed"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)[!WARNING] Trigger words: You should useFine Detailedto trigger the image generation.