Diffusers
Safetensors
OrbitQuantComponentArtifact
orbitquant
quantized
diffusion-transformer
8-bit precision
Instructions to use WaveCut/Wan2.1-T2V-1.3B-Diffusers-OrbitQuant-W4A4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Wan2.1-T2V-1.3B-Diffusers-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/Wan2.1-T2V-1.3B-Diffusers-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
| { | |
| "artifact_format": "orbitquant-v1", | |
| "source_model_id": "Wan-AI/Wan2.1-T2V-1.3B-Diffusers", | |
| "source_revision": "0fad780a534b6463e45facd96134c9f345acfa5b", | |
| "source_license": "apache-2.0", | |
| "quant_method": "orbitquant", | |
| "paper": "https://arxiv.org/abs/2607.02461", | |
| "weight_bits": 4, | |
| "activation_bits": 4, | |
| "rotation": "rpbh", | |
| "rotation_seed": 0, | |
| "block_size": "paper", | |
| "block_size_policy": "largest_power_of_two_dividing_dim", | |
| "codebook": "lloyd_max", | |
| "codebook_version": 2, | |
| "row_norm_dtype": "bfloat16", | |
| "runtime_mode": "auto_fused", | |
| "activation_kernel_backend": "auto", | |
| "activation_eps": 1e-10, | |
| "adaln_group_size": 64, | |
| "quantization_device": "cuda", | |
| "weight_quantization_backend": "triton_cuda", | |
| "quantization_staging_mode": "streaming", | |
| "target_policy": "wan", | |
| "adaln_policy": "int4_rtn_group64_bf16_activation", | |
| "quantized_modules": [ | |
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