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.gitattributes

@@ -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
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,128 @@
+---
+base_model: microsoft/AesCode-32B
+base_model_relation: finetune
+library_name: mlx
+pipeline_tag: image-text-to-text
+tags:
+- mlx
+- multimodal
+- vision
+- code-generation
+- html
+- apple-silicon
+language:
+- en
+license: apache-2.0
+---
+
+# AesCode-32B MLX bf16
+
+A faithful, full-precision (bfloat16) MLX conversion of
+[microsoft/AesCode-32B](https://huggingface.co/microsoft/AesCode-32B) for Apple
+Silicon, **with the vision tower kept intact**.
+
+AesCode-32B is a `Qwen3VLForConditionalGeneration` finetune of
+[Qwen/Qwen3-VL-32B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct)
+that turns a prompt plus a reference image into information-rich visual artifacts
+(slides, posters, dashboards, product pages) as HTML and CSS. It sees a screenshot
+and writes the code for it.
+
+This conversion changes nothing about the model's behavior. It is the same
+33.4B-parameter bf16 weights, re-sharded into MLX format so they load and run
+natively on an M-series Mac with no PyTorch and no cloud.
+
+## What is in this build
+
+| | |
+|---|---|
+| precision | bfloat16 (no quantization) |
+| vision | all 351 `vision_tower.*` tensors kept, `vision_config` and processor configs intact |
+| framework | runs with `mlx-vlm` on Apple Silicon |
+| size | about 62 GB on disk |
+
+## Vision was tested before upload
+
+A lot of MLX vision-language uploads are made with tools that only understand the
+language half, so the vision tower gets silently dropped and the model fails on
+the first image. This one was checked the hard way: a real screenshot of a live
+ineedhemp.com product page was fed in and the model was asked for an SEO,
+marketing and accessibility audit plus image alt-text.
+
+It read the real page. From its audit:
+
+> SEO: The page needs a clear title tag, probably "Divine Crossing v5 Rebuildable
+> Concentrate Heater - Divine Tribe" plus meta description. The breadcrumb and H1
+> are good, but adding schema markup for product, review, and offer would help
+> rich results.
+>
+> Marketing/Conversion: Strong points are the bold yellow CTA, clear price range,
+> star rating, and benefit-driven copy. The "just the cup, $8.42" section is
+> useful but visually buried.
+>
+> Alt-text: Main product image: "Divine Crossing v5 rebuildable concentrate heater
+> with ceramic cup and metal body." Thumbnail 2: "V5 logo and geometric design."
+
+It named the product, the breadcrumb, the star rating, the price range, the yellow
+add-to-cart button and a small pricing note buried far down the page, and wrote
+usable alt-text for each product photo. The vision path works.
+
+## Use
+
+```bash
+pip install mlx-vlm
+python -m mlx_vlm.generate --model divinetribe/AesCode-32B-MLX-bf16 \
+  --image screenshot.png \
+  --prompt "Recreate this screenshot as a single HTML file with inline CSS." \
+  --max-tokens 1200
+```
+
+Runs on an M-series Mac. No cloud inference, no API keys, no telemetry.
+
+## Benchmarks
+
+The most authoritative evaluation that actually covers this model is the one in
+AesCode's own paper, **"AesCode: Aesthetic Code Generation with Decoupled
+Cross-Modal Rewards"** ([arXiv:2610.18860](https://arxiv.org/abs/2610.18860)).
+There is no independent public leaderboard that lists AesCode specifically, so
+these numbers come straight from the authors' benchmark of 300 infographic-style
+samples, scored for rule-following correctness and visual quality. Scores quoted
+from the [model card](https://huggingface.co/microsoft/AesCode-32B):
+
+| Model (with reference image) | Overall | Visual |
+|---|---|---|
+| **AesCode-32B** | **85.89** | 77.44 |
+| Claude Opus 4.8 (no reference) | 76.78 | |
+| GPT-5.5 (no reference) | 76.31 | |
+| Qwen3-VL-32B base (with reference) | 61.10 | |
+
+AesCode-32B lifts visual quality over the same-scale Qwen3-VL baseline by 22.4
+points and lands in the range of the closed frontier models. For broader
+general-vision numbers on the backbone itself, see the official
+[Qwen3-VL](https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct) evaluations (that is
+the base model's benchmark, not AesCode's).
+
+## Credits
+
+This build stands entirely on other people's work. Credit where it is due:
+
+- **The AesCode team at Microsoft**, who created the model and the benchmark:
+  Xin Gao, Yifan Yang, Xin Li, Pan Wang, Yan Li, Muzhao Tian, Mingxi Cheng, Bei
+  Liu, Kai Qiu, Qi Dai, Dong Chen, Yue Dong, Leandros Tassiulas, Rex Ying, Ji Li
+  and Chong Luo. Paper: [arXiv:2610.18860](https://arxiv.org/abs/2610.18860),
+  model: [microsoft/AesCode-32B](https://huggingface.co/microsoft/AesCode-32B).
+- **The Qwen team at Alibaba**, for the
+  [Qwen3-VL-32B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct) base
+  that AesCode is built on.
+- **The MLX team at Apple** and **Prince Canuma** and the
+  [mlx-vlm](https://github.com/Blaizzy/mlx-vlm) contributors, whose open-source
+  work makes it possible to run a model like this natively and privately on a Mac.
+
+Thank you to all of them.
+
+## Note
+
+This is a faithful conversion for Apple Silicon. It does not add knowledge and it
+does not make output correct. You are responsible for what you build with it.
+
+Converted and published by [divinetribe](https://huggingface.co/divinetribe) ·
+[more models](https://nicedreamzwholesale.com/software/huggingface/)

added_tokens.json

@@ -0,0 +1,28 @@
+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|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
+}

chat_template.jinja

@@ -0,0 +1,120 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {%- if messages[0].content is string %}
+            {{- messages[0].content }}
+        {%- else %}
+            {%- for content in messages[0].content %}
+                {%- if 'text' in content %}
+                    {{- content.text }}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+        {{- '\n\n' }}
+    {%- endif %}
+    {{- "# 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' }}
+        {%- if messages[0].content is string %}
+            {{- messages[0].content }}
+        {%- else %}
+            {%- for content in messages[0].content %}
+                {%- if 'text' in content %}
+                    {{- content.text }}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- for message in messages %}
+    {%- if message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' }}
+        {%- if message.content is string %}
+            {{- message.content }}
+        {%- else %}
+            {%- for content in message.content %}
+                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
+                    <|vision_start|><|image_pad|><|vision_end|>
+                {%- elif content.type == 'video' or 'video' in content %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
+                    <|vision_start|><|video_pad|><|vision_end|>
+                {%- elif 'text' in content %}
+                    {{- content.text }}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role + '\n' }}
+        {%- if message.content is string %}
+            {{- message.content }}
+        {%- else %}
+            {%- for content_item in message.content %}
+                {%- if 'text' in content_item %}
+                    {{- content_item.text }}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and message.content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {%- if message.content is string %}
+            {{- message.content }}
+        {%- else %}
+            {%- for content in message.content %}
+                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
+                    <|vision_start|><|image_pad|><|vision_end|>
+                {%- elif content.type == 'video' or 'video' in content %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
+                    <|vision_start|><|video_pad|><|vision_end|>
+                {%- elif 'text' in content %}
+                    {{- content.text }}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+        {{- '\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 %}

config.json

@@ -0,0 +1,88 @@
+{
+    "architectures": [
+        "Qwen3VLForConditionalGeneration"
+    ],
+    "do_sample": true,
+    "dtype": "bfloat16",
+    "eos_token_id": [
+        151645,
+        151645,
+        151643
+    ],
+    "generation_config": {
+        "do_sample": true,
+        "eos_token_id": [
+            151645,
+            151645,
+            151643
+        ],
+        "pad_token_id": 151643,
+        "temperature": 0.7,
+        "top_k": 20,
+        "top_p": 0.8,
+        "transformers_version": "4.57.6"
+    },
+    "image_token_id": 151655,
+    "model_type": "qwen3_vl",
+    "pad_token_id": 151643,
+    "temperature": 0.7,
+    "text_config": {
+        "attention_bias": false,
+        "attention_dropout": 0.0,
+        "bos_token_id": 151643,
+        "dtype": "bfloat16",
+        "eos_token_id": 151645,
+        "head_dim": 128,
+        "hidden_act": "silu",
+        "hidden_size": 5120,
+        "initializer_range": 0.02,
+        "intermediate_size": 25600,
+        "max_position_embeddings": 262144,
+        "model_type": "qwen3_vl_text",
+        "num_attention_heads": 64,
+        "num_hidden_layers": 64,
+        "num_key_value_heads": 8,
+        "rms_norm_eps": 1e-06,
+        "rope_scaling": {
+            "mrope_interleaved": true,
+            "mrope_section": [
+                24,
+                20,
+                20
+            ],
+            "rope_type": "default"
+        },
+        "rope_theta": 5000000,
+        "use_cache": true,
+        "vocab_size": 151936
+    },
+    "tie_word_embeddings": false,
+    "top_k": 20,
+    "top_p": 0.8,
+    "transformers_version": "4.57.6",
+    "use_cache": false,
+    "video_token_id": 151656,
+    "vision_config": {
+        "deepstack_visual_indexes": [
+            8,
+            16,
+            24
+        ],
+        "depth": 27,
+        "dtype": "bfloat16",
+        "hidden_act": "gelu_pytorch_tanh",
+        "hidden_size": 1152,
+        "in_channels": 3,
+        "initializer_range": 0.02,
+        "intermediate_size": 4304,
+        "model_type": "qwen3_vl",
+        "num_heads": 16,
+        "num_position_embeddings": 2304,
+        "out_hidden_size": 5120,
+        "patch_size": 16,
+        "spatial_merge_size": 2,
+        "temporal_patch_size": 2
+    },
+    "vision_end_token_id": 151653,
+    "vision_start_token_id": 151652
+}

generation_config.json

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+{
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.57.6"
+}

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preprocessor_config.json

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+{
+  "crop_size": null,
+  "data_format": "channels_first",
+  "default_to_square": true,
+  "device": null,
+  "disable_grouping": null,
+  "do_center_crop": null,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_pad": null,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "Qwen2VLImageProcessorFast",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
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+  "input_data_format": null,
+  "max_pixels": null,
+  "merge_size": 2,
+  "min_pixels": null,
+  "pad_size": null,
+  "patch_size": 16,
+  "processor_class": "Qwen3VLProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "return_tensors": null,
+  "size": {
+    "longest_edge": 16777216,
+    "shortest_edge": 65536
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+  "temporal_patch_size": 2
+}

processor_config.json

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+{
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_processor_type": "Qwen3VLImageProcessor",
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
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+    "merge_size": 2,
+    "min_pixels": 65536,
+    "patch_size": 16,
+    "rescale_factor": 0.00392156862745098,
+    "temporal_patch_size": 2
+  },
+  "processor_class": "Qwen3VLProcessor",
+  "video_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "fps": 2,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
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+    "max_frames": 768,
+    "max_pixels": 25165824,
+    "merge_size": 2,
+    "min_frames": 4,
+    "min_pixels": 4096,
+    "patch_size": 16,
+    "rescale_factor": 0.00392156862745098,
+    "temporal_patch_size": 2,
+    "video_processor_type": "Qwen3VLVideoProcessor"
+  }
+}

special_tokens_map.json

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+{
+  "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
+  }
+}

tokenizer.json

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_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|>"
+  ],
+  "is_local": true,
+  "local_files_only": false,
+  "model_max_length": 262144,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "right",
+  "processor_class": "Qwen3VLProcessor",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

video_preprocessor_config.json

@@ -0,0 +1,41 @@
+{
+  "crop_size": null,
+  "data_format": "channels_first",
+  "default_to_square": true,
+  "device": null,
+  "do_center_crop": null,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "do_sample_frames": true,
+  "fps": 2,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "input_data_format": null,
+  "max_frames": 768,
+  "merge_size": 2,
+  "min_frames": 4,
+  "num_frames": null,
+  "pad_size": null,
+  "patch_size": 16,
+  "processor_class": "Qwen3VLProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "return_metadata": false,
+  "size": {
+    "longest_edge": 25165824,
+    "shortest_edge": 4096
+  },
+  "temporal_patch_size": 2,
+  "video_metadata": null,
+  "video_processor_type": "Qwen3VLVideoProcessor"
+}