Text-to-Image
Diffusers
lora
template:diffusion-lora
Dual-Character
Male
Female
3D-Character
Fine-Textured
Instructions to use strangerzonehf/Flux-3DXL-Partfile-C0001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use strangerzonehf/Flux-3DXL-Partfile-C0001 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("strangerzonehf/Flux-3DXL-Partfile-C0001") prompt = "3DXLC1, A close-up portrait of a man in a black tuxedo with a white collared shirt and a black bow tie. The mans hair is short and dark, and he has a slight smile on his face. His eyes are blue, and his lips are pink. The backdrop is a light gray, and the mans shadow is cast on the left side of the image." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
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<Gallery />
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## Trigger words
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<Gallery />
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## Model description for 3DXL Partfile 000C1
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Image Processing Parameters
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| Parameter | Value | Parameter | Value |
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|---------------------------|--------|---------------------------|--------|
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| LR Scheduler | constant | Noise Offset | 0.03 |
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| Optimizer | AdamW | Multires Noise Discount | 0.1 |
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| Network Dim | 64 | Multires Noise Iterations | 10 |
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| Network Alpha | 32 | Repeat & Steps | 15 & 2500 |
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| Epoch | 18 | Save Every N Epochs | 1 |
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Labeling: florence2-en(natural language & English)
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Total Images Used for Training : 17
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## Best Dimensions & Inference
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| **Dimensions** | **Aspect Ratio** | **Recommendation** |
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|-----------------|------------------|---------------------------|
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| 1280 x 832 | 3:2 | Best |
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| 1024 x 1024 | 1:1 | Default |
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### Inference Range
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- **Recommended Inference Steps:** 30–35
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## Setting Up
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```python
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import torch
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from pipelines import DiffusionPipeline
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base_model = "black-forest-labs/FLUX.1-dev"
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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lora_repo = "strangerzonehf/Flux-3DXL-Partfile-C0001"
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trigger_word = "3DXLC1"
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pipe.load_lora_weights(lora_repo)
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device = torch.device("cuda")
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pipe.to(device)
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```
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## Trigger words
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