Image-Text-to-Video
Diffusers
Safetensors
text-to-video
image-to-video
video-to-video
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
video-to-audio-video
audio-to-audio-video
audio-video-generation
multimodal
synchronized-audio-video
reference-to-audio-video
Instructions to use MiniMaxAI/MiniMax-H3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MiniMaxAI/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("MiniMaxAI/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
Huge Thanks for Using a Single-Stream Transformer, Porting It to a Multi-GPU ComfyUI Setup with RayLight Is a Breeze
#24
by komixenon - opened
Implementing sequence parallelism is quite easy because we do not have to deal with any weird packing and unpacking of audio, latent, and text sequences. Once the sequence enters the core model’s forward pass, only odd-length padding is necessary.
komixenon changed discussion title from Huge Thanks for Using a Single-Stream Transformer—Porting It to a Multi-GPU ComfyUI Setup with RayLight Is a Breeze to Huge Thanks for Using a Single-Stream Transformer, Porting It to a Multi-GPU ComfyUI Setup with RayLight Is a Breeze