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The bare call inside _build_prompt_context would raise NameError because class methods don't close over class-level scope. Use instead to trigger attribute lookup. Update enrich_hf_metadata prompt.md clue locations for better LLM accuracy. Update baseline report to v2 (mean 69.0, 46 models, +2.2pp vs baseline 71.1%). Consolidate README snapshots into baselines/readmes/.
4.4 KiB
4.4 KiB
tags, widget, base_model, instance_prompt, license
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black-forest-labs/FLUX.1-dev | Long toons | creativeml-openrail-m |
Flux-Long-Toon-LoRA
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/Flux-Long-Toon-LoRA
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 | 25 & 3270 |
| Epoch | 18 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 15
Best Dimensions
- 768 x 1024 (Best)
- 1024 x 1024 (Default)
Setting Up
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-Long-Toon-LoRA"
trigger_word = "Long toons"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words
You should use Long toons to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.