prithivMLmods
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README.md
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<Gallery />
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## Sample Image
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![prithivMLmods/SD3.5-Large-Anime-LoRA](images/444.webp)
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![prithivMLmods/SD3.5-Large-Anime-LoRA](images/555.webp)
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## Trigger words
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You should use `Anime 35` to trigger the image generation.
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## Download model
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<Gallery />
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**The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.**
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## Model description
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**prithivMLmods/SD3.5-Large-Anime-LoRA**
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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 | 25 & 2.7K |
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| Epoch | 15 | Save Every N Epochs | 1 |
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Labeling: florence2-en(natural language & English)
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Total Images Used for Training : 23
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## Setting up
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```python
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import torch
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from diffusers import StableDiffusion3Pipeline
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pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large", torch_dtype=torch.bfloat16)
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pipe.load_lora_weights("prithivMLmods/SD3.5-Large-Anime-LoRA", weight_name="SD3.5-Large-Anime-LoRA.safetensors")
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pipe.fuse_lora(lora_scale=1.0)
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pipe.to("cuda")
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prompt = "Man in the style of dark beige and brown, uhd image, youthful protagonists, nonrepresentational photography"
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negative_prompt = "(lowres, low quality, worst quality)"
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image = pipe(prompt=prompt,
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negative_prompt=negative_prompt
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num_inference_steps=24,
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guidance_scale=4.0,
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width=960, height=1280,
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).images[0]
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image.save(f"example.jpg")
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```
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## Sample Image
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![prithivMLmods/SD3.5-Large-Anime-LoRA](images/444.webp)
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![prithivMLmods/SD3.5-Large-Anime-LoRA](images/555.webp)
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## Trigger words 🧨
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> [!WARNING]
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> **Trigger words:** You should use `Anime 35` to trigger the image generation.
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## Download model
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