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strangerzonehf
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Model Details
Model Provider
strangerzonehf
Model Tree
black-forest-labs/FLUX.1-dev
Input Modalities
Output Modalities
Supported Functionality
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 | 35 & 4700 |
| Epoch | 22 | Save Every N Epochs | 1 |
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Labeling: florence2-en(natural language & English)Total Images Used for Training : 50 [ 10@5 ] [ Hi -Res ] python
import torchfrom pipelines import DiffusionPipeline base_model = "black-forest-labs/FLUX.1-dev"pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16) lora_repo = "strangerzonehf/Flux-Animeo-v1-LoRA"trigger_word = "Animeo" pipe.load_lora_weights(lora_repo) device = torch.device("cuda")pipe.to(device)You should use Animeo to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
import torchfrom pipelines import DiffusionPipeline base_model = "black-forest-labs/FLUX.1-dev"pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16) lora_repo = "strangerzonehf/Flux-Animeo-v1-LoRA"trigger_word = "Animeo" pipe.load_lora_weights(lora_repo) device = torch.device("cuda")pipe.to(device)