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: 647 Bytes
fa2d87b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | from __future__ import annotations
def inventory_failure(
component_mode: str, *, orbit_count: int, adaln_count: int, cache_count: int
) -> str | None:
if cache_count:
return "full dequantized caches present after clean load"
low_bit_count = orbit_count + adaln_count
if component_mode == "w4a4" and low_bit_count == 0:
return "no low-bit modules restored"
if component_mode == "source_copy" and low_bit_count:
return "unexpected low-bit modules in source component copy"
if component_mode not in {"w4a4", "source_copy"}:
return f"unknown component mode: {component_mode}"
return None
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