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Commit
587f45f
·
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1 Parent(s): 8aa2271

Requantize W2A3 with mixed-width low-bit protection

Browse files
README.md CHANGED
@@ -19,20 +19,9 @@ OrbitQuant is a calibration-free post-training quantization method for image and
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  Install OrbitQuant and the Hugging Face runtime dependencies:
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  ```bash
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- pip install "orbitquant[hf,kernels]>=0.6.0"
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  ```
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- The optimized native kernel package is provisioned automatically at first
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- model load: OrbitQuant derives the runtime variant (torch minor and CUDA
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- version for CUDA, the torch stable ABI for CPU, plus OS and architecture),
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- downloads the matching prebuilt wheel from the
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- [OrbitQuant kernels release](https://github.com/iamwavecut/OrbitQuant/releases/tag/kernels-v1)
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- with checksum verification, and caches it under `~/.cache/orbitquant/kernels`.
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- Without a matching variant, CUDA inference falls back to the Triton packed
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- path. Run `orbitquant kernels-install` to provision explicitly. For ComfyUI,
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- the [ComfyUI-OrbitQuant](https://github.com/iamwavecut/ComfyUI-OrbitQuant)
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- node pack provisions the same kernels from its install hook.
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-
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  Download this model repository as an OrbitQuant artifact, then load the source Diffusers pipeline with the quantized component patched in:
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  ```python
@@ -158,6 +147,7 @@ The matrix uses all ten prompts from `image_visual_v2` at `1024x1024`. BF16 and
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  - Method: `orbitquant`
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  - Bits: `W2A3`
 
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  - Runtime mode: `auto_fused`
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  - Activation kernel backend: `auto`
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  - Activation normalization epsilon: `1e-10`
@@ -179,10 +169,6 @@ The matrix uses all ten prompts from `image_visual_v2` at `1024x1024`. BF16 and
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  - Calibration data: none
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  - Text encoders and VAE: left in source precision by default
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- ## Observed Quality
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-
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- **Warning:** The OrbitQuant W2A3 outputs show severe visual collapse across all ten native comparison prompts. Use W3A3 or W4A4 for this model.
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-
186
  ## Visual Comparison
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188
  The following assets are stored in this artifact and compare the BF16 base generation against the OrbitQuant generation with the same prompt and seed.
 
19
  Install OrbitQuant and the Hugging Face runtime dependencies:
20
 
21
  ```bash
22
+ pip install "orbitquant[hf,kernels]>=0.4.0"
23
  ```
24
 
 
 
 
 
 
 
 
 
 
 
 
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  Download this model repository as an OrbitQuant artifact, then load the source Diffusers pipeline with the quantized component patched in:
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27
  ```python
 
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  - Method: `orbitquant`
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  - Bits: `W2A3`
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+ - Module weight-width counts: `W2: 44, W3: 110, W4: 84`
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  - Runtime mode: `auto_fused`
152
  - Activation kernel backend: `auto`
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  - Activation normalization epsilon: `1e-10`
 
169
  - Calibration data: none
170
  - Text encoders and VAE: left in source precision by default
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  ## Visual Comparison
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  The following assets are stored in this artifact and compare the BF16 base generation against the OrbitQuant generation with the same prompt and seed.
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252
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1532
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1672
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1742
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1812
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1882
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1952
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2162
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2232
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2302
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2372
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2429
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2442
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2499
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2512
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2533
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2539
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2557
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2569
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2579
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2582
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2600
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2603
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2606
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2609
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2612
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2615
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2618
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2621
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2627
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2639
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2645
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2649
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2652
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2656
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2658
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2667
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2670
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2679
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2697
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2709
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2718
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2721
  ]
2722
  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2723
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20
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23
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+ },
2919
  "checksums": {
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+ "assets/image_generation_comparison_matrix.webp": "8f4235baa433900bfaf3ac5160af91c0ed68c25fffa02958f19d0a1b9dc3e421",
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+ "benchmark/summary.json": "119fadb02071c014a9c51c1108a54e20fa3532b0eaa39c2a57b788787ecbd38c",
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+ "model.safetensors": "667324a633b4e4d92931ca523943c093da46c24472d3f7dc315782ca57847585",
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+ "model_index.json": "cffb8406914ef65f5bb4df0c893e680c39f4c99ab4d6629f4457f61797ee33b3",
2924
+ "orbitquant_codebooks.safetensors": "e7737934089114db3107ba8c16e8c6a882f259fc97d02352cf5f4fb1b0656fe9",
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  "orbitquant_rotations.safetensors": "e1724c9394bf83ea05da6b457b8072d2bcb3d5a533dafce916da8deb517d3825",
2926
+ "prompts.json": "f48aca6d4d681d1ed10dcce8ad43fedb965b4a6a4b11003eb5e37ea53e4eb526",
2927
+ "quantization_config.json": "6b778e6789a13a9e44c795571fc7d524d775730b602b634b87ba6c511d21e784"
2928
  }
2929
  }
prompts.json CHANGED
@@ -49,19 +49,19 @@
49
  "id": "cyrillic-text-rendering",
50
  "title": "08 Russian Constructivist typography",
51
  "category": "russian_typography",
52
- "prompt": "A richly detailed Russian Constructivist science-fiction poster with the exact Cyrillic headline \"КВАНТОВАЯ ОРБИТА\", the exact subtitle \"МОСКВА 2049\", and a small exact stamp \"КВАНТОВАНИЕ\"; diagonal red and black geometry, cream paper, cosmonaut portrait, orbital diagrams, halftone grain, folded corners, layered ink, museum archival photograph, all letters crisp and correctly ordered"
53
  },
54
  {
55
  "id": "style-heavy",
56
  "title": "09 Japanese typography and mixed style",
57
  "category": "japanese_typography",
58
- "prompt": "An elaborate Japanese art magazine cover combining Edo woodblock printing with a futuristic Tokyo skyline, with the exact vertical title \"量子の軌道\" and the exact subtitle \"東京の未来\"; giant indigo waves curl around glass towers, red-crowned cranes cross a gold moon, tiny pedestrians and trains fill the lower streets, visible washi fibers, layered spot colors, precise Japanese glyphs, balanced editorial layout"
59
  },
60
  {
61
  "id": "occlusion-reflection",
62
  "title": "10 Chinese typography, reflection, occlusion",
63
  "category": "chinese_typography_reflection_occlusion",
64
- "prompt": "A luxurious Chinese retro-futurist department-store window at night with the exact gold title \"量子轨道\" and the exact red subtitle \"未来之城\"; a curved chrome robot is partly occluded by peonies and blue-and-white porcelain, the calligraphy and neon street must appear coherently reflected across its body, multiple glass layers, silk textures, passing bicycles, cinematic rain, fine product-photography detail"
65
  }
66
  ]
67
  }
 
49
  "id": "cyrillic-text-rendering",
50
  "title": "08 Russian Constructivist typography",
51
  "category": "russian_typography",
52
+ "prompt": "A richly detailed Russian Constructivist science-fiction poster with the exact Cyrillic headline \"\u041a\u0412\u0410\u041d\u0422\u041e\u0412\u0410\u042f \u041e\u0420\u0411\u0418\u0422\u0410\", the exact subtitle \"\u041c\u041e\u0421\u041a\u0412\u0410 2049\", and a small exact stamp \"\u041a\u0412\u0410\u041d\u0422\u041e\u0412\u0410\u041d\u0418\u0415\"; diagonal red and black geometry, cream paper, cosmonaut portrait, orbital diagrams, halftone grain, folded corners, layered ink, museum archival photograph, all letters crisp and correctly ordered"
53
  },
54
  {
55
  "id": "style-heavy",
56
  "title": "09 Japanese typography and mixed style",
57
  "category": "japanese_typography",
58
+ "prompt": "An elaborate Japanese art magazine cover combining Edo woodblock printing with a futuristic Tokyo skyline, with the exact vertical title \"\u91cf\u5b50\u306e\u8ecc\u9053\" and the exact subtitle \"\u6771\u4eac\u306e\u672a\u6765\"; giant indigo waves curl around glass towers, red-crowned cranes cross a gold moon, tiny pedestrians and trains fill the lower streets, visible washi fibers, layered spot colors, precise Japanese glyphs, balanced editorial layout"
59
  },
60
  {
61
  "id": "occlusion-reflection",
62
  "title": "10 Chinese typography, reflection, occlusion",
63
  "category": "chinese_typography_reflection_occlusion",
64
+ "prompt": "A luxurious Chinese retro-futurist department-store window at night with the exact gold title \"\u91cf\u5b50\u8f68\u9053\" and the exact red subtitle \"\u672a\u6765\u4e4b\u57ce\"; a curved chrome robot is partly occluded by peonies and blue-and-white porcelain, the calligraphy and neon street must appear coherently reflected across its body, multiple glass layers, silk textures, passing bicycles, cinematic rain, fine product-photography detail"
65
  }
66
  ]
67
  }
quantization_config.json CHANGED
@@ -15,6 +15,8 @@
15
  "target_policy": "z_image",
16
  "adaln_policy": "int4_rtn",
17
  "adaln_group_size": 64,
 
 
18
  "modules_to_not_convert": [],
19
  "modules_dtype_dict": {},
20
  "artifact_format_version": 1,
@@ -23,5 +25,11 @@
23
  "packed_matmul_block_m": 64,
24
  "packed_matmul_block_n": 64,
25
  "packed_matmul_block_k": 128,
26
- "packed_matmul_num_warps": 4
 
 
 
 
 
 
27
  }
 
15
  "target_policy": "z_image",
16
  "adaln_policy": "int4_rtn",
17
  "adaln_group_size": 64,
18
+ "modules_to_convert": [],
19
+ "modules_to_use_adaln": [],
20
  "modules_to_not_convert": [],
21
  "modules_dtype_dict": {},
22
  "artifact_format_version": 1,
 
25
  "packed_matmul_block_m": 64,
26
  "packed_matmul_block_n": 64,
27
  "packed_matmul_block_k": 128,
28
+ "packed_matmul_num_warps": 4,
29
+ "weight_row_tile_size": 256,
30
+ "w4a4_int8_weight_cache": false,
31
+ "lowbit_boundary_protection": "auto",
32
+ "lowbit_protected_blocks": 4,
33
+ "lowbit_protected_bits": 4,
34
+ "lowbit_interior_protection": true
35
  }