Instructions to use Rin247/MiniMax-H3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rin247/MiniMax-H3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Rin247/MiniMax-H3", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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These media packages have been forged and optimized in the MECHA Forge.
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Each one holds the Denoiser, Text Encoder, and VAE components packaged together for easier deployment.
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## Available quantizations
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| Quant | Denoiser | Text encoder | VAE |
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These media packages have been forged and optimized in the MECHA Forge.
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Each one holds the Denoiser, Text Encoder, and VAE components packaged together for easier deployment.
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## Description
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MiniMax H3: multimodal (audio+video) generation. 25 steps, CFG 7.0.
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## Available quantizations
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| Quant | Denoiser | Text encoder | VAE |
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