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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+img/collage.jpg filter=lfs diff=lfs merge=lfs -text

Qwen-Image-2512/model_index.json

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Qwen-Image-2512/scheduler/scheduler_config.json

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Qwen-Image-2512/text_encoder/config.json

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Qwen-Image-2512/text_encoder/generation_config.json

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+    "visual.merger.ln_q.weight": "model-00001-of-00004.safetensors",
+    "visual.merger.mlp.0.bias": "model-00001-of-00004.safetensors",
+    "visual.merger.mlp.0.weight": "model-00001-of-00004.safetensors",
+    "visual.merger.mlp.2.bias": "model-00001-of-00004.safetensors",
+    "visual.merger.mlp.2.weight": "model-00001-of-00004.safetensors",
+    "visual.patch_embed.proj.weight": "model-00001-of-00004.safetensors"
+  }
+}

Qwen-Image-2512/tokenizer/added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

Qwen-Image-2512/tokenizer/chat_template.jinja

@@ -0,0 +1,54 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

Qwen-Image-2512/tokenizer/special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

Qwen-Image-2512/tokenizer/tokenizer_config.json

@@ -0,0 +1,207 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

Qwen-Image-2512/vae/config.json

@@ -0,0 +1,56 @@
+{
+  "_class_name": "AutoencoderKLQwenImage",
+  "_diffusers_version": "0.36.0.dev0",
+  "attn_scales": [],
+  "base_dim": 96,
+  "dim_mult": [
+    1,
+    2,
+    4,
+    4
+  ],
+  "dropout": 0.0,
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README.md

@@ -1,3 +1,215 @@
 ---
+library_name: diffusers
 license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen-Image-2512/blob/main/LICENSE
+pipeline_tag: text-to-image
+base_model:
+- Qwen/Qwen-Image-2512
+tags:
+- qwen-image
+- text-to-image
+- image-generation
+- vllm
+- vllm-omni
+- humming
+- byteshape
 ---
+
+# Qwen-Image-2512 Humming (ShapeLearn Quantized, vLLM-Omni)
+
+This is a quantized version of **Qwen-Image-2512** for the **[vLLM-Omni](https://github.com/vllm-project/vllm-omni)** backend with optimized **Humming kernels**, the fastest way we ship this model. Quantization was produced with **ByteShape's ShapeLearn**, which learns the optimal datatype per tensor to maintain high quality even at very low bitlengths.
+
+> **Experimental.** We tested this flow with vLLM 0.24.0, vLLM-Omni 0.24.0, `vllm-omni-humming` 0.3.0, and `humming-kernels` 0.1.11 on NVIDIA 30-, 40-, and 50-series and RTX Pro 6000 GPUs. **Linux and NVIDIA only** (SM75+, driver ≥ 575).
+
+Six sizes are available, from **17.29 GB (6.77 bpw)** down to **7.83 GB (3.07 bpw)**. All variants generate high-quality images.
+
+Each package bundles the text encoder, VAE, scheduler, and tokenizer, so there are no separate component downloads: you pick a size and serve.
+
+> Prefer ComfyUI or a wider hardware range? We also publish GGUF builds of the same model for ComfyUI and `stable-diffusion.cpp`: [byteshape/Qwen-Image-2512-GGUF](https://huggingface.co/byteshape/Qwen-Image-2512-GGUF).
+
+To learn more about ShapeLearn, and for the full walkthrough with screenshots and a downloadable ComfyUI workflow, visit our [blog](https://byteshape.com/blogs/Qwen-Image-2512/).
+
+If you have questions or want to share feedback, reach us on [Reddit](https://www.reddit.com/r/ByteShape/).
+
+## A Note on Speed
+
+Unlike the decoding stage of an LLM, diffusion inference is **not** heavily constrained by memory bandwidth. Compressing the model therefore does not necessarily make image generation faster. Quantization here buys you **VRAM headroom**, not throughput. Backend optimization is what moves the needle.
+
+This backend uses optimized Humming kernels and is roughly **2-3x faster** than the GGUF path. On an RTX 5090 each step takes around **0.5 seconds**, so a 20-step image samples in about **10 seconds**.
+
+| Backend | Time per step (RTX 5090) | Time for 20 steps |
+|---|---|---|
+| **vLLM-Omni** (this repo) | \~0.5 s | \~10 s |
+| [GGUF](https://huggingface.co/byteshape/Qwen-Image-2512-GGUF) | \~1.2 s | \~24 s |
+
+For measured peak VRAM and end-to-end times for **every size at four output resolutions**, with and without CPU offload, see the [VRAM and speed table](https://byteshape.com/blogs/Qwen-Image-2512/#requirements) in the blog post.
+
+## What Do the Sizes Look Like?
+
+![One prompt rendered by BF16 and all six Humming sizes, with a matching close-up crop of the ring face under each variant](img/collage.jpg)
+
+Quality does not fall off a cliff as the bits come off. BF16, 6.77 and 5.33 bpw are near-interchangeable on this prompt, down to the same scratch fan and specular streak; from 4.70 bpw a soft grey haze spreads across the ring face and the surviving scratches grow thicker and fewer at each step, and at 3.07 bpw the composition itself drifts, with a narrower band sitting higher in the frame; even there the image is still a clean macro shot. Differences like these are subtle and highly prompt-dependent, and the row above is one prompt out of 24.
+
+Judge for yourself: the [blog post](https://byteshape.com/blogs/Qwen-Image-2512/) walks through the full set, and the [interactive comparison explorer](https://byteshape.com/blogs/Qwen-Image-2512/comparison/) lets you A/B any two variants across 24 curated prompts at full resolution, with a slider, zoom, and a curator note for each prompt. If you read the outputs differently, tell us on [Reddit](https://www.reddit.com/r/ByteShape/).
+
+## Repository Layout
+
+The package is a shared **shell** (the pipeline) plus a pool of **transformers**, one per size:
+
+```
+Qwen-Image-2512/          # the shell: text encoder, VAE, scheduler, tokenizer
+quantized_models/
+  6.77bpw/transformer/
+  5.33bpw/transformer/
+  4.70bpw/transformer/
+  4.18bpw/transformer/
+  3.57bpw/transformer/
+  3.07bpw/transformer/
+```
+
+You download the shell once, then drop the transformer of your choice into it.
+
+## Available Models
+
+| Model ID | Bits/Weight | Transformer Size | Folder |
+|---|---|---|---|
+| VLLM-1 | 3.07 | 7.83 GB | `quantized_models/3.07bpw` |
+| VLLM-2 | 3.57 | 9.11 GB | `quantized_models/3.57bpw` |
+| VLLM-3 | 4.18 | 10.68 GB | `quantized_models/4.18bpw` |
+| VLLM-4 | 4.70 | 12.00 GB | `quantized_models/4.70bpw` |
+| VLLM-5 | 5.33 | 13.60 GB | `quantized_models/5.33bpw` |
+| VLLM-6 | 6.77 | 17.29 GB | `quantized_models/6.77bpw` |
+
+**On VRAM.** The size above is the diffusion transformer only. The shell adds a **BF16 text encoder (\~16.6 GB)** and the VAE (\~0.25 GB), so keeping everything resident on the GPU needs roughly `transformer + 17 GB`: about 25 GB for the smallest size and 34 GB for the largest.
+
+- **≤ 32 GB cards (including the RTX 5090):** serve with `--enable-cpu-offload`. All six sizes work; the text encoder lives in system RAM.
+- **48 GB and larger (e.g. RTX Pro 6000):** drop `--enable-cpu-offload` for full speed.
+
+**Selection rule:** take the largest model that comfortably fits your card. Since compression does not speed up diffusion, there is little reason to go smaller than your VRAM allows.
+
+## Quick Start
+
+### 1. Set up the environment
+
+```bash
+conda create -y -n qwen-image-humming python=3.12
+conda activate qwen-image-humming
+
+# torch trio (cu129)
+pip install torch==2.11.0 torchvision==0.26.0 torchaudio==2.11.0 \
+  --index-url https://download.pytorch.org/whl/cu129
+
+# vLLM 0.24.0 (cu129 wheel)
+printf 'torch==2.11.0+cu129\ntorchvision==0.26.0+cu129\ntorchaudio==2.11.0+cu129\n' > constraints.txt
+PIP_CONSTRAINT=constraints.txt pip install \
+  https://github.com/vllm-project/vllm/releases/download/v0.24.0/vllm-0.24.0+cu129-cp38-abi3-manylinux_2_28_x86_64.whl
+
+# vLLM-Omni + our loader plugin
+PIP_CONSTRAINT=constraints.txt pip install vllm-omni==0.24.0
+PIP_CONSTRAINT=constraints.txt pip install vllm-omni-humming==0.3.0
+
+# humming kernels: must be >= 0.1.11 (older versions produce corrupted images)
+pip install --no-deps "humming-kernels>=0.1.11"
+```
+
+`vllm-omni-humming` is our own plugin, and it is the one required extra piece for this path: stock vLLM-Omni cannot read a pre-quantized Humming checkpoint on its own. The plugin registers itself and detects our models from their `transformer/config.json`.
+
+### 2. Download the model
+
+Grab the shell and the size you want:
+
+```bash
+pip install -U huggingface_hub
+
+# the shell + one transformer (here the 3.07 bpw size)
+huggingface-cli download byteshape/Qwen-Image-2512-Humming \
+  --include "Qwen-Image-2512/*" "quantized_models/3.07bpw/*" \
+  --local-dir Qwen-Image-2512-Humming
+cd Qwen-Image-2512-Humming
+```
+
+Then drop your chosen transformer into the shell. The folder is already named `transformer`, so it lands with the correct name:
+
+```bash
+# symlink it in (instant, no extra disk) ...
+ln -sfn ../quantized_models/3.07bpw/transformer Qwen-Image-2512/transformer
+
+# ... or move it in (a real, self-contained model dir)
+mv quantized_models/3.07bpw/transformer Qwen-Image-2512/transformer
+```
+
+To try a different size later, swap the symlink, or move one transformer out and another in. The folders are named by bit-width (`6.77bpw`, `4.18bpw`, `3.07bpw`, and so on).
+
+### 3. Serve
+
+From the folder root:
+
+```bash
+vllm-omni serve Qwen-Image-2512 \
+  --omni --served-model-name Qwen/Qwen-Image-2512 \
+  --enable-cpu-offload --port 8124
+```
+
+Keep `--enable-cpu-offload` on cards with ≤ 32 GB (an RTX 5090 needs it); drop it on larger GPUs for full speed.
+
+Do **not** pass `--diffusion-quantization-config` or set any `VLLM_HUMMING_*` variables. The plugin drives everything from the checkpoint.
+
+The first serve on a new GPU spends a few minutes compiling kernels for your card, then caches them.
+
+### 4. Generate
+
+The server exposes the OpenAI images API:
+
+```bash
+curl -s http://127.0.0.1:8124/v1/images/generations \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "Qwen/Qwen-Image-2512",
+    "prompt": "A red panda on a mossy log at dawn",
+    "size": "1024x1024",
+    "num_inference_steps": 20,
+    "true_cfg_scale": 2.5,
+    "negative_prompt": " ",
+    "seed": 1234
+  }' \
+  | python3 -c "import sys,json,base64; d=json.load(sys.stdin); open('out.png','wb').write(base64.b64decode(d['data'][0]['b64_json']))"
+```
+
+**Always include a `negative_prompt`, even a single space.** vLLM-Omni applies classifier-free guidance only when a negative prompt is present with `true_cfg_scale > 1`; with none, guidance is skipped and the image comes out flatter and lower-contrast.
+
+## Driving the Server from ComfyUI
+
+If you prefer a GUI over `curl`, the `ComfyUI-vLLM-Omni` custom node sends generation requests to a running vLLM-Omni server, local or remote. ComfyUI is only the front end; vLLM still does the work.
+
+Install the node into your ComfyUI installation:
+
+```bash
+cd /path/to/ComfyUI/custom_nodes
+git clone https://github.com/vllm-project/vllm-omni.git
+cp -r vllm-omni/apps/ComfyUI-vLLM-Omni ComfyUI-vLLM-Omni
+rm -rf vllm-omni
+```
+
+Restart ComfyUI (`python main.py`), then open a browser and go to **http://127.0.0.1:8188** to reach the ComfyUI interface. A new **vLLM-Omni** folder appears in the **Node Library** sidebar. No extra Python packages are needed beyond ComfyUI's own.
+
+Keep the vLLM-Omni server from step 3 running. ComfyUI reaches it at `http://127.0.0.1:8124/v1`. If ComfyUI runs on a different machine, use the server's address instead of `127.0.0.1`.
+
+For the workflow, download `qwen-image-humming-vllm-omni.json` from our [blog post](https://byteshape.com/blogs/Qwen-Image-2512/) and load it with **`Ctrl+O`**, or start from ComfyUI's built-in template at **sidebar → Templates → vLLM-Omni → vLLM-Omni Image Generation**.
+
+In the **Generate Image** node, set:
+
+- **url** → `http://127.0.0.1:8124/v1`
+- **model** → `Qwen/Qwen-Image-2512`
+- **prompt** / **negative_prompt** → your text (negative: at least a space)
+- **width** / **height** → e.g. 1024 x 1024
+
+In the attached **Diffusion Sampling Params** node, set the seed, `num_inference_steps` (e.g. 20), and `true_cfg_scale` (e.g. 2.5), then run the workflow.
+
+## Troubleshooting
+
+| Symptom | Cause and fix |
+|---|---|
+| `HummingConfig ... unexpected keyword argument`, or a shape mismatch on `img_mod.1` / `txt_mod.1` at load | The plugin is not installed in the active environment. Check with `pip show vllm-omni-humming`. |
+| Grainy or speckled images | The Humming kernels are too old. Reinstall with `pip install --no-deps "humming-kernels>=0.1.11"`. |
+| Flat, low-contrast images | No `negative_prompt` was sent, so CFG was skipped. Pass one; a single space is enough. |
+| Out of memory on serve | Add `--enable-cpu-offload`, or pick a smaller bit-width from the table above. |

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