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--- |
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tags: |
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- text-to-image |
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- lora |
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- diffusers |
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- template:diffusion-lora |
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- flux-dev |
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- ultra |
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- realism |
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- photorealism |
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- hi-res |
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- face |
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- diffusion |
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widget: |
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- text: >- |
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Woman in a red jacket, snowy, in the style of hyper-realistic portraiture, |
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caninecore, mountainous vistas, timeless beauty, palewave, iconic, |
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distinctive noses --ar 72:101 --stylize 750 --v 6 |
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output: |
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url: images/3.png |
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- text: >- |
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Photograph, candid shot, famous randomly couch and randomly finished with randomly cats, center point for cat, Use camera is Canon EOS 5D Mark IV with a Canon EF 24mm f/1.4L II USM lens, set at aperture f/2.8 for a depth of field that highlights the furniture clean lines with rich and many detail, randomly color and finished, soft ambient light, studio light setting, ultra realistic, UHD, many details --chaos 1 --ar 9:16 --style raw --stylize 750 |
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output: |
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url: images/5.png |
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- text: >- |
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High-resolution photograph, woman, UHD, photorealistic, shot on a Sony A7III --chaos 20 --ar 1:2 --style raw --stylize 250 |
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output: |
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url: images/4.png |
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base_model: black-forest-labs/FLUX.1-dev |
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instance_prompt: Ultra realistic |
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license: creativeml-openrail-m |
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--- |
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# Canopus-LoRA-Flux-UltraRealism-2.0 |
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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/Canopus-LoRA-Flux-FaceRealism** |
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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 | 30 & 3.8K+ | |
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| Epoch | 20 | Save Every N Epochs | 1 | |
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Labeling: florence2-en(natural language & English) |
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Total Images Used for Training : 70 [ Hi-RES ] & More ............... |
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## Trigger words |
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You should use `Ultra realistic` to trigger the image generation. |
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## Other Versions |
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Here’s a table format for the Hugging Face model **"prithivMLmods/Canopus-LoRA-Flux-FaceRealism"**: |
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| **Attribute** | **Details** | |
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|---------------------------|--------------------------------------------------------------------------------------------------------------| |
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| **Model Name** | Canopus-LoRA-Flux-FaceRealism | |
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| **Model ID** | `prithivMLmods/Canopus-LoRA-Flux-FaceRealism` | |
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| **Hugging Face URL** | [Canopus-LoRA-Flux-FaceRealism](https://huggingface.co./prithivMLmods/Canopus-LoRA-Flux-FaceRealism) | |
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| **Model Type** | LoRA (Low-Rank Adaptation) | |
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| **Primary Use Case** | Face Realism image generation | |
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| **Supported Framework** | Hugging Face Diffusers | |
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| **Data Type** | `bfloat16`, `fp16`, `float32` | |
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| **Compatible Models** | Stable Diffusion, Flux models | |
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| **Model Author** | `prithivMLmods` | |
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| **LoRA Technique** | LoRA for image style transfer with a focus on generating realistic faces | |
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| **Model Version** | Latest | |
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| **License** | Open-Access | |
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| **Tags** | LoRA, Face Realism, Flux, Image Generation | |
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## Setting Up |
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``` |
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import torch |
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from pipelines import DiffusionPipeline |
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base_model = "prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0" |
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16) |
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lora_repo = "prithivMLmods/Canopus-LoRA-Flux-FaceRealism" |
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trigger_word = "Ultra realistic" # Leave trigger_word blank if not used. |
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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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## Download model |
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Weights for this model are available in Safetensors format. |
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[Download](/prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0/tree/main) them in the Files & versions tab. |
