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README.md
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This LoRA is an attempt at improving on the overall detail of generations from Hunyuan. It focus in particular on things such as improved depth of field, realistic skin texture, and better lighting.
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It works at generating both realistic short video clips and single frames for images.
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## Video Examples
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/641ba2eeec5b871c0bcfdba3/bKisU-fni9hZIfm-dpwWu.mp4"></video>
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/641ba2eeec5b871c0bcfdba3/5zUD6bzyLWd2WiJY9F65U.png)
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## Additional Info
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[Full Video Demonstration](https://www.youtube.com/watch?v=0tuGBrDbXU0)
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This LoRA is an attempt at improving on the overall detail of generations from Hunyuan. It focus in particular on things such as improved depth of field, realistic skin texture, and better lighting.
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It works at generating both realistic short video clips and single frames for images.
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At the moment, the candidate LoRA used here is overtrained. It is recommended to use a strength of around 0.6. You will also need to experiment a lot with the seeds, guidance, steps, and resolution. Try to keep steps over 35 and minimum resolution above 512x512. Guidance seems to work to varying degrees between 3.5-12.5. Higher guidance and strength may lead to more similarities in things such as scene and characters. You will want to experiment with lowering the guidance and strength while raising the resolution when you run into lots of distortion.
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## Video Examples
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/641ba2eeec5b871c0bcfdba3/bKisU-fni9hZIfm-dpwWu.mp4"></video>
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/641ba2eeec5b871c0bcfdba3/5zUD6bzyLWd2WiJY9F65U.png)
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## Training Details
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I used around 150 images only for this initial LoRA. I focused on public domain photos from around the early 2010s.
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- epochs = 600
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- gradient_accumulation_steps = 4
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- warmup_steps = 100
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#### Adapter
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- type = "lora"
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- rank = 32
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- dtype = "bfloat16"
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- only_double_blocks = true
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#### Optimizer
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- type = "adamw_optimi"
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- lr = 0.0002
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- betas = [ 0.9, 0.99,]
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- weight_decay = 0.01
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- eps = 1e-8
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## Additional Info
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[Full Video Demonstration](https://www.youtube.com/watch?v=0tuGBrDbXU0)
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