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
File size: 539 Bytes
fa2d87b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"status": "pass",
"component": "transformer",
"component_mode": "w4a4",
"framework": "diffusers",
"class_name": "MiniMaxH3Transformer3DModel",
"load_seconds": 7.063924089074135,
"orbitquant_module_count": 300,
"adaln_int4_module_count": 50,
"bf16_linear_module_count": 20,
"full_dequantized_cache_count": 0,
"resident_state_bytes": 19948278784,
"quantization_config": null,
"rss_peak_bytes": 5341511680,
"gpu_peak_allocated_bytes": 0,
"gpu": "NVIDIA RTX PRO 6000 Blackwell Server Edition",
"pid": 40091
}
|