Studio Ghibli Style 🎥 Wan2.1-T2V-14B
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Studio Ghibli Style 🎥 Wan2.1-T2V-14B
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Studio Ghibli Style 🎥 Wan2.1-T2V-14B

I am very happy to share my magnum opus LoRA, which I've been working on for the past month since Wan came out. This is the best LoRA on Civitai I have ever trained, and I have to say once again - WanVideo is an amazing model.

I'm currently writing a detailed post about the training process and will update the model page soon enough.

I'll also be adding TONS of showcase videos this week and next because, honestly, I keep getting high-quality clips from nearly any prompt I feed into it.

I'm sorry in advance for the number of visually similar clips in the gallery - it's just that I usually generate three clips per prompt, and most of the time, all 3 turn out perfect (from my POV, of course). I just can't decide which one is the best, so I end up keeping them all.

This LoRA was trained for ~90 hours on an RTX 3090 with musubi-tuner using a mixed dataset of 240 clips and 120 images. It could have been done faster, but I was obsessed with pushing the limits to create a state-of-the-art style model. It’s up to you to decide if I succeeded.

Usage
The trigger phrase is Studio Ghibli style - all training captions were prefixed with these words.

All clips I publish in gallery are raw model outputs using a single LoRA, without post-processing, upscaling, or interpolation.

Workflows are embedded with each clip. You can download example workflow (JSON) here: https://files.catbox.moe/1nrkms.json

I apply a lot of optimizations, including fp8_e5m2 checkpoints + torch.compile, TeaCache, Enhance-A-video, Fp16_fast, SLG, and (sometimes) Zero-Star. Rendering a 640x480x81 clip takes about 5 minutes (RTX 3090).


This model is sourced from an external transfer (transfer address: https://civitai.com/models/1404755/studio-ghibli-style-wan21-t2v-14b ),if the original author has objections to this transfer, you can click,
Appeal
We will, within 24 hours, edit, delete, or transfer the model to the original author according to the original author's request

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Model Information

Original author:
seruva19
Model Type:
LoRA
Basic Model:
WAN2.1
Trigger Words:
Studio Ghibli style

I am very happy to share my magnum opus LoRA, which I've been working on for the past month since Wan came out. This is the best LoRA on Civitai I have ever trained, and I have to say once again - WanVideo is an amazing model.

I'm currently writing a detailed post about the training process and will update the model page soon enough.

I'll also be adding TONS of showcase videos this week and next because, honestly, I keep getting high-quality clips from nearly any prompt I feed into it.

I'm sorry in advance for the number of visually similar clips in the gallery - it's just that I usually generate three clips per prompt, and most of the time, all 3 turn out perfect (from my POV, of course). I just can't decide which one is the best, so I end up keeping them all.

This LoRA was trained for ~90 hours on an RTX 3090 with musubi-tuner using a mixed dataset of 240 clips and 120 images. It could have been done faster, but I was obsessed with pushing the limits to create a state-of-the-art style model. It’s up to you to decide if I succeeded.

Usage
The trigger phrase is Studio Ghibli style - all training captions were prefixed with these words.

All clips I publish in gallery are raw model outputs using a single LoRA, without post-processing, upscaling, or interpolation.

Workflows are embedded with each clip. You can download example workflow (JSON) here: https://files.catbox.moe/1nrkms.json

I apply a lot of optimizations, including fp8_e5m2 checkpoints + torch.compile, TeaCache, Enhance-A-video, Fp16_fast, SLG, and (sometimes) Zero-Star. Rendering a 640x480x81 clip takes about 5 minutes (RTX 3090).


This model is sourced from an external transfer (transfer address: https://civitai.com/models/1404755/studio-ghibli-style-wan21-t2v-14b ),if the original author has objections to this transfer, you can click,
Appeal
We will, within 24 hours, edit, delete, or transfer the model to the original author according to the original author's request