Upload SpatialAxiom-9B model weights and configs

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+figures/spatialaxiom_logo.png filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

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README.md

@@ -1,3 +1,278 @@
 ---
+library_name: transformers
 license: cc-by-nc-4.0
+license_link: https://creativecommons.org/licenses/by-nc/4.0/
+pipeline_tag: image-text-to-text
+base_model:
+- Qwen/Qwen3.5-9B
 ---
+
+# SpatialAxiom-9B
+
+<p align="center">
+  <img width="400px" src="figures/spatialaxiom_logo.png">
+</p>
+
+<p align="center">
+  <a href="https://d2i-ai.github.io/SpatialAxiom/"><img src="https://img.shields.io/badge/%F0%9F%8C%90%20Homepage-14b87a" alt="Homepage"></a>
+  <a href="https://huggingface.co/yokinglou/SpatialAxiom-35B-A3B"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20SpatialAxiom--35B--A3B-ffd21e" alt="SpatialAxiom-35B-A3B"></a>
+</p>
+
+## Introduction
+
+We are thrilled to release **SpatialAxiom**, an open spatial intelligence model for general spatial reasoning that achieves significant advances in 3D relational inference, perspective taking, multi-view correspondence, and embodied video understanding. Built on the Qwen3.5 VLM family without altering the base architecture, SpatialAxiom derives its strength from a spatial data-centric training recipe: a systematic taxonomy of spatial tasks, balanced task distribution, and data synthesis to raise data quality, applied to large-scale spatial supervision spanning indoor scenes, egocentric views, and multi-camera settings. Trained purely with full-parameter SFT, SpatialAxiom serves as a clean starting point for further post-training. We release two open-weight models: **SpatialAxiom-9B**, a compact dense model, and **SpatialAxiom-35B-A3B**, a mixture-of-experts model with 3B active parameters.
+
+## Highlights
+
+- **Leading spatial reasoning**: On average, our models surpass proprietary models and larger open-source alternatives, with leading results on VSI-Bench, MMSI-Bench, MindCube, ViewSpatial, and EmbSpatial.
+
+- **Spatial data-centric training recipe**: A systematic taxonomy of spatial tasks, balanced task distribution, and data synthesis to raise data quality. SpatialAxiom is trained purely with full-parameter SFT and serves as a clean starting point for downstream fine-tuning or RL.
+
+- **Qwen3.5 VLM backbone**: Inherits the Qwen3.5 vision-language model architecture, preserving a general-purpose multimodal design without task-specific architectural modifications.
+
+- **Open-weight release**: SpatialAxiom-9B and SpatialAxiom-35B-A3B are publicly released on Hugging Face, compatible with `transformers` and `vLLM` out of the box.
+
+![Average Score](figures/spatialaxiom_average_score.png)
+
+
+![Benchmark Results](figures/spatialaxiom_benchmark_score.png)
+
+
+## Model Overview
+
+- Type: Causal Language Model with Vision Encoder
+- Training Stage: Pre-training & Post-training
+- Language Model
+    - Number of Parameters: 9B
+    - Hidden Dimension: 4096
+    - Token Embedding: 248320 (Padded)
+    - Number of Layers: 32
+    - Hidden Layout: 8 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN))
+    - Gated DeltaNet:
+        - Number of Linear Attention Heads: 32 for V and 16 for QK
+        - Head Dimension: 128
+    - Gated Attention:
+        - Number of Attention Heads: 16 for Q and 4 for KV
+        - Head Dimension: 256
+        - Rotary Position Embedding Dimension: 64
+    - Feed Forward Network:
+        - Intermediate Dimension: 12288
+    - LM Output: 248320 (Padded)
+    - MTP: trained with multi-steps  
+- Context Length: 262,144 natively and extensible up to 1,010,000 tokens.
+
+## Spatial Benchmark Results
+
+
+| Rank | Model | **Avg** | VSI-Bench | MMSI-Bench | MindCube | ViewSpatial | SITE | BLINK | 3DSR | EmbSpatial |
+| ---: | --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
+| 1 | **SpatialAxiom-35B-A3B** | **70.8** | **72.8** | 50.0 | 91.7 | 66.8 | 56.4 | 75.8 | 66.3 | **86.6** |
+| 2 | **SpatialAxiom-9B** | 70.6 | 70.2 | **51.8** | **92.5** | **70.6** | 53.3 | 76.9 | 64.2 | 85.1 |
+| 3 | Gemini-3.5-Flash | 69.2 | 63.1 | 50.7 | 77.6 | 56.0 | 70.6 | **80.0** | **72.5** | 83.1 |
+| 4 | Qwen3.7-Plus | 66.6 | 63.3 | 45.0 | 68.6 | 54.9 | **71.3** | 76.0 | 69.7 | 83.8 |
+| 5 | Gemini-3.1-Pro | 66.5 | 57.5 | 49.5 | 76.4 | 53.1 | 67.0 | 77.3 | 67.3 | 84.0 |
+| 6 | SenseNova-SI-1.5-InternVL3-8B | 64.4 | 67.3 | 38.3 | 92.1 | 59.0 | 47.5 | 69.5 | 61.1 | 80.4 |
+| 7 | Qwen3.6-27B | 61.6 | 59.8 | 41.1 | 59.9 | 51.5 | 66.0 | 70.6 | 60.7 | 83.4 |
+| 8 | Kimi-K2.6 | 61.3 | 54.9 | 37.9 | 67.4 | 46.7 | 63.6 | 75.2 | 64.1 | 80.8 |
+| 9 | Qwen3.5-35B-A3B | 61.2 | 58.1 | 41.9 | 63.5 | 50.8 | 61.4 | 70.5 | 59.8 | 83.6 |
+| 10 | GPT-5.5 | 60.7 | 60.4 | 42.2 | 65.5 | 46.5 | 58.3 | 73.3 | 59.0 | 80.3 |
+| 11 | Qwen3.6-35B-A3B | 60.5 | 56.0 | 40.2 | 60.4 | 50.7 | 63.4 | 69.3 | 60.0 | 83.8 |
+| 12 | Gemma-4-31B | 57.2 | 48.1 | 37.0 | 63.3 | 45.3 | 58.0 | 70.3 | 54.4 | 81.0 |
+| 13 | Qwen3.5-9B | 55.9 | 54.3 | 38.7 | 57.6 | 48.2 | 42.3 | 67.6 | 56.8 | 81.5 |
+| 14 | Seed1.6 | 54.2 | 49.9 | 38.3 | 48.8 | 43.9 | 54.6 | 65.9 | 56.9 | 75.4 |
+| 15 | InternVL3.5-8B | 49.0 | 56.1 | 29.0 | 40.2 | 40.0 | 43.8 | 58.2 | 49.2 | 75.7 |
+| 16 | Gemma-4-26B-A4B | 47.8 | 32.9 | 29.2 | 48.8 | 41.7 | 39.7 | 63.8 | 53.6 | 72.3 |
+| 17 | BAGEL-7B-MoT | 45.3 | 31.4 | 31.0 | 34.7 | 41.3 | 37.0 | 63.6 | 50.2 | 73.1 |
+| 18 | Cambrian-S-7B | 45.1 | 62.9 | 27.1 | 37.9 | 41.3 | 36.1 | 37.9 | 45.0 | 72.8 |
+
+## Quickstart
+
+> [!Important]
+> SpatialAxiom-9B is fine-tuned from Qwen3.5-9B for **direct (non-thinking) responses only**.
+> It does not produce thinking blocks (no chain-of-thought wrapped in special tags). Do not enable thinking mode at inference time (`enable_thinking` must remain `false`). The model does not support `/think` or `/nothink` soft switches.
+
+### Transformers (image)
+
+The latest `transformers` with Qwen3.5 VLM support is required. Make sure `torchvision` and `pillow` are installed.
+
+```python
+from transformers import AutoModelForMultimodalLM, AutoProcessor
+
+model_id = "<HF_REPO_ID>"
+model = AutoModelForMultimodalLM.from_pretrained(
+    model_id, dtype="bfloat16", device_map="auto"
+)
+processor = AutoProcessor.from_pretrained(model_id)
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image", "url": "room.jpg"},
+            {
+                "type": "text",
+                "text": "If I stand at the door facing the bed, is the chair to my left or right?",
+            },
+        ],
+    }
+]
+
+inputs = processor.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    tokenize=True,
+    return_dict=True,
+    return_tensors="pt",
+    enable_thinking=False,
+).to(model.device)
+
+out = model.generate(**inputs, max_new_tokens=32768)
+print(
+    processor.batch_decode(
+        out[:, inputs["input_ids"].shape[1]:], skip_special_tokens=True
+    )[0]
+)
+```
+
+### Transformers (video)
+
+```python
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "video", "url": "https://example.com/walkthrough.mp4"},
+            {
+                "type": "text",
+                "text": "Estimate the size of the room in square meters and describe the route taken.",
+            },
+        ],
+    }
+]
+# Same apply_chat_template / generate flow as above.
+```
+
+### Serving with vLLM
+
+[vLLM](https://github.com/vllm-project/vllm) is recommended for production serving. A recent vLLM build with Qwen3.5 support is required, which can be installed in a fresh environment with:
+
+```shell
+uv pip install vllm --torch-backend=auto --extra-index-url https://wheels.vllm.ai/nightly
+```
+
+```shell
+vllm serve <HF_REPO_ID> \
+  --port 8000 \
+  --tensor-parallel-size 1 \
+  --max-model-len 65536 \
+  --default-chat-template-kwargs '{"enable_thinking": false}' \
+  --served-model-name spatialaxiom-9b
+```
+
+This creates an OpenAI-compatible API at `http://localhost:8000/v1`. If you encounter OOM errors, reduce `--max-model-len` (e.g. to 32768). For multi-view or long-video spatial tasks, 32K–64K context is typically sufficient.
+
+
+### OpenAI-compatible API
+
+Install the OpenAI SDK and point it at your vLLM server:
+
+```shell
+pip install -U openai
+
+export OPENAI_BASE_URL="http://localhost:8000/v1"
+export OPENAI_API_KEY="EMPTY"
+```
+
+#### Image input
+
+```python
+from openai import OpenAI
+
+client = OpenAI()
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image_url", "image_url": {"url": "https://example.com/room.jpg"}},
+            {
+                "type": "text",
+                "text": "If I stand at the door facing the bed, is the chair to my left or right?",
+            },
+        ],
+    }
+]
+
+chat_response = client.chat.completions.create(
+    model="spatialaxiom-9b",
+    messages=messages,
+    max_tokens=32768,
+    temperature=0,
+    top_p=0.95,
+)
+print(chat_response.choices[0].message.content)
+```
+
+#### Video input
+
+```python
+from openai import OpenAI
+
+client = OpenAI()
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "video_url",
+                "video_url": {"url": "https://example.com/walkthrough.mp4"},
+            },
+            {
+                "type": "text",
+                "text": "Describe the spatial layout and the route taken through the room.",
+            },
+        ],
+    }
+]
+
+# Video frame sampling (vLLM): default fps=2, do_sample_frames=True.
+# Customizing fps via extra_body requires launching vLLM with
+# --media-io-kwargs '{"video": {"num_frames": -1}}'.
+chat_response = client.chat.completions.create(
+    model="spatialaxiom-9b",
+    messages=messages,
+    max_tokens=32768,
+    temperature=0,
+    top_p=0.95,
+    extra_body={
+        "mm_processor_kwargs": {"fps": 2, "do_sample_frames": True},
+    },
+)
+print(chat_response.choices[0].message.content)
+```
+
+If the vLLM server was **not** launched with `--default-chat-template-kwargs '{"enable_thinking": false}'`, add it per request:
+
+```python
+extra_body={
+    "chat_template_kwargs": {"enable_thinking": False},
+}
+```
+
+
+
+
+### Citation
+
+If you find our work helpful, feel free to give us a cite.
+
+```bibtex
+@misc{spatialaxiom,
+    title  = {SpatialAxiom: An Open Spatial Intelligence Model for General Spatial Reasoning},
+    author = {Lou, Yujing and Chen, Pingyi and Cao, Shen and Gu, Jiaqi and Guo, Jinhui and Tong, Jintao and Hao, Yunzhuo and Liu, Yao and Fan, Lubin and Wu, Yue and Ye, Jieping},
+    month  = {July},
+    year   = {2026},
+    url    = {https://d2i-ai.github.io/SpatialAxiom}
+}
+```

chat_template.jinja

@@ -0,0 +1,154 @@
+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,114 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "eos_token_id": 248046,
+  "hidden_size": 4096,
+  "image_token_id": 248056,
+  "model_type": "qwen3_5",
+  "pad_token_id": 248044,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": null,
+    "dtype": "bfloat16",
+    "eos_token_id": 248044,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 12288,
+    "layer_types": [
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention"
+    ],
+    "linear_conv_kernel_dim": 4,
+    "linear_key_head_dim": 128,
+    "linear_num_key_heads": 16,
+    "linear_num_value_heads": 32,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 262144,
+    "mlp_only_layers": [],
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 4,
+    "pad_token_id": 248044,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+      "mrope_interleaved": true,
+      "mrope_section": [
+        11,
+        11,
+        10
+      ],
+      "partial_rotary_factor": 0.25,
+      "rope_theta": 10000000,
+      "rope_type": "default"
+    },
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.2.0",
+  "use_cache": true,
+  "video_token_id": 248057,
+  "vision_config": {
+    "deepstack_visual_indexes": [],
+    "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_5",
+    "num_heads": 16,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 4096,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 248054,
+  "vision_start_token_id": 248053,
+  "_name_or_path": "SpatialAxiom-9B"
+}

generation_config.json

@@ -0,0 +1,9 @@
+{
+  "_from_model_config": true,
+  "eos_token_id": [
+    248044,
+    248046
+  ],
+  "transformers_version": "5.2.0",
+  "use_cache": true
+}

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preprocessor_config.json

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+{
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+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
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+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

processor_config.json

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+{
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+    "data_format": "channels_first",
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
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+    "image_processor_type": "Qwen2VLImageProcessorFast",
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+    "patch_size": 16,
+    "resample": 3,
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+      "shortest_edge": 65536
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+  "video_processor": {
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+    "default_to_square": true,
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+    "do_normalize": true,
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+    "return_metadata": false,
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+      "shortest_edge": 4096
+    },
+    "temporal_patch_size": 2,
+    "video_processor_type": "Qwen3VLVideoProcessor"
+  }
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4
+size 19989343

tokenizer_config.json

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+  "add_prefix_space": false,
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+    "248044": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "special": true
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+      "content": "<|image_pad|>",
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+      "single_word": false,
+      "special": true
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+      "single_word": false,
+      "special": true
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+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n    {%- if content is string %}\n        {{- content }}\n    {%- elif content is iterable and content is not mapping %}\n        {%- for item in content %}\n            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain images.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Picture ' ~ image_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n            {%- elif 'video' in item or item.type == 'video' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain videos.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Video ' ~ video_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n            {%- elif 'text' in item %}\n                {{- item.text }}\n            {%- else %}\n                {{- raise_exception('Unexpected item type in content.') }}\n            {%- endif %}\n        {%- endfor %}\n    {%- elif content is none or content is undefined %}\n        {{- '' }}\n    {%- else %}\n        {{- raise_exception('Unexpected content type.') }}\n    {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n    {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {{- '<|im_start|>system\\n' + content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" %}\n        {%- set content = render_content(message.content, false)|trim %}\n        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n            {%- set ns.multi_step_tool = false %}\n            {%- set ns.last_query_index = index %}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n    {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n    {%- set content = render_content(message.content, true)|trim %}\n    {%- if message.role == \"system\" %}\n        {%- if not loop.first %}\n            {{- raise_exception('System message must be at the beginning.') }}\n        {%- endif %}\n    {%- elif message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- set reasoning_content = reasoning_content|trim %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if tool_call.function is defined %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {%- if loop.first %}\n                    {%- if content|trim %}\n                        {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- else %}\n                        {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- endif %}\n                {%- else %}\n                    {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                {%- endif %}\n                {%- if tool_call.arguments is defined %}\n                    {%- for args_name, args_value in tool_call.arguments|items %}\n                        {{- '<parameter=' + args_name + '>\\n' }}\n                        {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}\n                        {{- args_value }}\n                        {{- '\\n</parameter>\\n' }}\n                    {%- endfor %}\n                {%- endif %}\n                {{- '</function>\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Unexpected message role.') }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- else %}\n        {{- '<think>\\n' }}\n    {%- endif %}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 262144,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "add_bos_token": false,
+  "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+  "extra_special_tokens": {
+    "audio_bos_token": "<|audio_start|>",
+    "audio_eos_token": "<|audio_end|>",
+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
+    "vision_bos_token": "<|vision_start|>",
+    "vision_eos_token": "<|vision_end|>"
+  }
+}

video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}