Castor-3D-Sketchfab-Flux-LoRA
| Property | Value |
|---|---|
| License | CreativeML OpenRAIL-M |
| Base Model | black-forest-labs/FLUX.1-dev |
| Training Images | 39 |
| Network Architecture | LoRA (64 dim, 32 alpha) |
What is Castor-3D-Sketchfab-Flux-LoRA?
Castor-3D-Sketchfab-Flux-LoRA is a specialized LoRA model designed to generate 3D Sketchfab-style images. Built on the FLUX.1-dev base model, it employs carefully tuned parameters for optimal 3D object generation. The model is currently in training phase and represents an evolving solution for creating detailed 3D visualizations.
Implementation Details
The model utilizes a constant learning rate scheduler with AdamW optimizer, featuring a network dimension of 64 and alpha of 32. Training specifications include a noise offset of 0.03, multires noise discount of 0.1, and 10 noise iterations across 10 epochs. The training process incorporated florence2-en labeling for natural language processing in English.
- Optimized for 3D object generation with specific trigger word "3D Sketchfab"
- Implements bfloat16 precision for efficient processing
- Trained with 1.8k steps and 23 repeats per epoch
- Supports CUDA acceleration for enhanced performance
Core Capabilities
- Generation of detailed 3D object visualizations
- Specialized in creating Sketchfab-style renderings
- Support for complex scene composition with multiple elements
- Background and lighting manipulation capabilities
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in generating 3D Sketchfab-style images with a specific focus on detailed object rendering. Its unique training parameters and specialized architecture make it particularly effective for creating 3D visualizations with precise control over object placement and composition.
Q: What are the recommended use cases?
The model is ideal for generating 3D object visualizations, architectural renderings, product demonstrations, and scene compositions. It works best when used with the trigger word "3D Sketchfab" and detailed prompting for specific object characteristics.
