Diffusers
Safetensors
OrbitQuantComponentArtifact
orbitquant
quantized
diffusion-transformer
8-bit precision
Instructions to use WaveCut/FLUX.2-klein-4B-OrbitQuant-W2A4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/FLUX.2-klein-4B-OrbitQuant-W2A4 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/FLUX.2-klein-4B-OrbitQuant-W2A4", 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: 2,562 Bytes
d16e497 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | {
"suite": "flux2-native",
"model_id": "black-forest-labs/FLUX.2-klein-4B",
"prompt": "A blue cube beside a yellow sphere and a green pyramid on a gray table",
"seed": 0,
"height": 1024,
"width": 1024,
"frames": null,
"steps": 4,
"guidance": 1.0,
"bit_settings": [
"W4A4",
"W3A3",
"W2A4",
"W2A3"
],
"device": "cuda",
"runtime_device": {
"requested_device": "cuda",
"resolved_device_type": "cuda",
"cuda_available": true,
"cuda_active": true,
"cuda_device_index": 0,
"cuda_device_name": "NVIDIA RTX PRO 6000 Blackwell Server Edition",
"cuda_device_capability": [
12,
0
],
"cuda_memory_allocated_bytes": 17040533504,
"cuda_memory_reserved_bytes": 22443720704,
"cuda_peak_memory_allocated_bytes": 19604974592
},
"dtype": "bfloat16",
"pipeline_class": "Flux2KleinPipeline",
"scheduler": {
"class": "FlowMatchEulerDiscreteScheduler",
"config": {
"num_train_timesteps": 1000,
"shift": 3.0,
"use_dynamic_shifting": true,
"base_shift": 0.5,
"max_shift": 1.15,
"base_image_seq_len": 256,
"max_image_seq_len": 4096,
"invert_sigmas": false,
"shift_terminal": null,
"use_karras_sigmas": false,
"use_exponential_sigmas": false,
"use_beta_sigmas": false,
"time_shift_type": "exponential",
"stochastic_sampling": false,
"_class_name": "FlowMatchEulerDiscreteScheduler",
"_diffusers_version": "0.37.0.dev0"
}
},
"wall_time_seconds": 1.6692825159989297,
"peak_vram_bytes": 19604974592,
"contact_sheet_path": null,
"quantization": {
"config": {
"quant_method": "orbitquant",
"weight_bits": 2,
"activation_bits": 4,
"rotation": "rpbh",
"rotation_seed": 0,
"block_size": "paper",
"codebook": "lloyd_max",
"codebook_dtype": "float32",
"row_norm_dtype": "bfloat16",
"activation_norm_dtype": "float32",
"activation_eps": 1e-12,
"weight_pack_dtype": "uint8",
"target_policy": "flux2",
"adaln_policy": "int4_rtn",
"adaln_group_size": 64,
"modules_to_not_convert": [],
"modules_dtype_dict": {},
"artifact_format_version": 1,
"runtime_mode": "dequant_bf16",
"activation_kernel_backend": "triton_cuda"
},
"summary": null,
"prewarm": {
"orbitquant_modules": 100,
"adaln_modules": 3,
"total_modules": 103,
"elapsed_seconds": 0.37310984497889876,
"device": "cuda",
"dtype": "bfloat16"
}
}
}
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