zhangccccc/Minimax_h3_latent_Upscaler

AI model by zhangccccc

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English · 中文 Neural latent-space upscaler for Minimax H3 video generation. Works directly on Minimax H3's 24-channel VAE latents to upscale spatial resolution (H×W) while preserving the time dimension. This model is designed to accelerate high-resolution H3 video generation: By skipping the expensive decode → pixel upscale → encode round-trip through Minimax H3's heavy 5B-parameter VAE, this pipeline saves a significant amount of generation time. It also avoids the ghosting / double-image artifacts that naive latent interpolation (bilinear/bicubic) introduces. Video upscale comparison — click to play: (If the player doesn't render, download the video here.) Image upscale comparison: The current release is v1. Its three checkpoints live together in minimaxh3latentupscaler3dconvv1/: All three checkpoints share the same 3D-convolution architecture. Pick the precision that matches your GPU and workflow. config.json at the repository root is the family index: it records what every release shares (the 24-channel H3 latent space and its normalization,…

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Model overview

zhangccccc/Minimax_h3_latent_Upscaler is a task-unspecified model repository published by zhangccccc on Hugging Face. The source reports the minimax-h3 library.

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Task: Not reported
Library: minimax-h3
Recent downloads (30 days): 0
Cumulative likes: 0
Hugging Face trending score: 0
Reported safetensors parameters: Not reported
Architecture: Not reported
License: apache-2.0
Access: Not gated by Hugging Face
Created: 2026-09-29T06:03:11.000Z
Last modified: 2026-09-29T06:03:11.000Z

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