Image-Text-to-Video
Diffusers
Safetensors
orbitquant
comfyui
w4
w4a4
native-w4a4-transformer-runtime
text-to-video
audio-video-generation
8-bit precision
Instructions to use WaveCut/MiniMax-H3-OrbitQuant-W4A4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/MiniMax-H3-OrbitQuant-W4A4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/MiniMax-H3-OrbitQuant-W4A4", 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
| { | |
| "status": "pass", | |
| "component": "vae", | |
| "component_mode": "source_copy", | |
| "framework": "diffusers", | |
| "class_name": "AutoencoderKLMiniMaxH3", | |
| "load_seconds": 0.1990923248231411, | |
| "orbitquant_module_count": 0, | |
| "adaln_int4_module_count": 0, | |
| "bf16_linear_module_count": 218, | |
| "full_dequantized_cache_count": 0, | |
| "resident_state_bytes": 10415475936, | |
| "quantization_config": null, | |
| "rss_peak_bytes": 856510464, | |
| "gpu_peak_allocated_bytes": 0, | |
| "gpu": "NVIDIA RTX PRO 6000 Blackwell Server Edition", | |
| "pid": 40911 | |
| } | |