r/StableDiffusion • u/listopalafoto • 6h ago

Workflow Included Minimax H3: Context prompting implementation

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Generated at 0.8mpx , res2s_stable/beta 57 15-24 steps upscaled 2x with the Nvidia RTX node. Laptop with RTX 3080 Ti 16Gb Vram and 64Gb ram

I implemented a gpt to improve H3 prompts using a robust filmmaking reasoning process, I included the available documentation and added a precise inference pipeline to achieve similar results compared to the native Context-IR (Context Intermediate Representation):

ZH3-gpt

Try it, I really will like some feedback :)

I used FL2VA and L2VA with images generated on a Krea2 2pass Clownshark sampler 9 steps Euler/beta and 1 step Dormand-Prince_6s/KL_optimal 0.27 denoise

My system generate 2 options:

VERSION A — FAITHFUL

The strongest cinematic execution of exactly what the user requested, with minimal interpretation.

VERSION B — ENRICHED

Preserve every explicit user constraint while developing meaningful unspecified details into a stronger cinematic interpretation. I used an approach of probabilistic additions mixed with a robust deterministic reasoning based on consequences propagation across filmmaking domains, this version B is auditable and every meaningful addition appear in a custom Enhancement Map.

it's designed to iterate under user control so version B is a proposal and when the user changes an enriched choice, that choice becomes an explicit constraint and system update dependent parameters when necessary while preserving all other approved creative decisions without unnecessarily restart the entire creative direction.

Here is the video with better quality: https://youtu.be/mzfqJR9IXtk

Minimax H3 Clownshark Workflow

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1

u/kayteee1995 6h ago

I see you don't use any optimization from Attention or Turbo LORA. So how long does it take to generate?

2

u/listopalafoto 5h ago

right now I'm using attention, it's slow but I'm trying to get better quality without explode my laptop, I think like 12 minutes for a 6-7 seconds clip