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

README.md

@@ -0,0 +1,237 @@
+---
+license: apache-2.0
+language:
+  - en
+  - zh
+base_model: Qwen/Qwen3-27B
+pipeline_tag: image-text-to-text
+library_name: transformers
+tags:
+  - judge-model
+  - text-to-image
+  - evaluation
+  - benchmark
+  - qwen
+---
+
+# Q-Judger
+
+<p align="center">
+  <a href="TODO"><img src="https://img.shields.io/badge/Paper-arXiv-b31b1b?logo=arxiv" alt="Paper"></a>
+  <a href="https://github.com/QwenLM/Qwen-Image-Bench"><img src="https://img.shields.io/badge/GitHub-Repo-blue?logo=github" alt="GitHub"></a>
+  <a href="https://huggingface.co/Qwen/Qwen-Image-Bench"><img src="https://img.shields.io/badge/Judge_Model-HuggingFace-ffd21e?logo=huggingface" alt="Model"></a>
+  <a href="https://huggingface.co/datasets/Qwen/Qwen-Image-Bench"><img src="https://img.shields.io/badge/Dataset-HuggingFace-ffd21e?logo=huggingface" alt="Dataset"></a>
+  <a href="https://www.modelscope.cn/datasets/Qwen/Qwen-Image-Bench"><img src="https://img.shields.io/badge/Dataset-ModelScope-624aff?logo=data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjIyIiBoZWlnaHQ9IjIyMiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj48cGF0aCBkPSJNNzEuNTU2IDcyLjg4OGgzOC42Njd2MzguNjY3SDcxLjU1NnpNMTExLjU1NiAxMTIuODg4aDM4LjY2N3YzOC42NjdoLTM4LjY2N3pNNzEuNTU2IDExMi44ODhoMzguNjY3djM4LjY2N0g3MS41NTZ6IiBmaWxsPSIjNjI0QUZGIi8+PC9zdmc+" alt="ModelScope"></a>
+</p>
+
+A fine-tuned judge model for evaluating text-to-image (T2I) generation quality. Built on top of Qwen3.6-27B, it scores generated images across **5 hierarchical dimensions** using structured checklists and outputs JSON-formatted evaluation results.
+
+## Links
+
+| Resource | Link |
+|----------|------|
+| 📑 Paper | TODO |
+| 📊 Benchmark Dataset (HuggingFace) | https://huggingface.co/datasets/Qwen/Qwen-Image-Bench |
+| 📊 Benchmark Dataset (ModelScope) | https://www.modelscope.cn/datasets/Qwen/Qwen-Image-Bench |
+| 💻 GitHub | https://github.com/QwenLM/Qwen-Image-Bench |
+| 🧑‍⚖️ Q-Judger Model | https://huggingface.co/Qwen/Qwen-Image-Bench |
+
+## Model Description
+
+Q-Judger is a vision-language model fine-tuned specifically for automated evaluation of text-to-image generated images. Given a text prompt and a generated image, the model evaluates the image on fine-grained quality criteria organized in a 3-level hierarchy and outputs structured JSON scores.
+
+- **Base Model**: Qwen3.6-27B
+- **Task**: Image quality evaluation / judging
+- **Input**: Text prompt + generated image
+- **Output**: Structured JSON with per-dimension scores (0 = Fail, 1 = Pass, 2 = Excel, N/A)
+- **Thinking Mode**: Enabled — the model uses chain-of-thought reasoning before producing the final JSON output
+
+## Evaluation Dimensions
+
+The model evaluates images across **5 top-level dimensions**, each with multiple sub-dimensions:
+
+### Quality
+- **Realism**: Physical Logic, Material Texture
+- **Detail**: Noise, Edge Clarity, Naturalness
+- **Resolution**: Resolution
+
+### Aesthetics
+- **Composition**: Composition
+- **Color Harmony**: Color Harmony
+- **Lighting**: Lighting & Atmosphere
+- **Anatomical Portraiture**: Anatomical Fidelity
+- **Emotional Expression**: Emotional Expression
+- **Style Control**: Style Control
+
+### Alignment
+- **Attributes**: Quantity, Facial Expression, Material Properties, Color, Shape, Size
+- **Actions**: Contact Interaction, Non-contact Interaction, Full-body Action
+- **Layout**: 2D Space, 3D Space
+- **Relations**: Composition Relationship, Difference/Similarity, Containment
+- **Scene**: Real-world Scene, Virtual Scene
+
+### Real-world Fidelity
+- **Fairness**: Social Bias, Cultural Fairness
+- **Safety & Compliance**: Safety & Compliance
+- **World Knowledge**: Animals, Objects, Information Visualization, Temporal Characteristics, Cultural Elements
+
+### Creative Generation
+- **Imagination**: Imagination
+- **Feature Matching**: Feature Matching
+- **Logical Resolution**: Logical Resolution
+- **Text Rendering**: Text Accuracy, Text Layout, Font, Cross-lingual Generation
+- **Design Applications**: Graphic Design, Product Design, Spatial Design, Fashion Styling, Game Design, Art Design
+- **Visual Storytelling**: Cinematic Style, Camera / Lens Style, Storyboard Creation, Shot Sizes, Composition, Angles, Comic Creation
+
+## Scoring Methodology
+
+### Raw Score Mapping
+
+| Raw Score | Meaning | Mapped Score |
+|-----------|---------|--------------|
+| 0 | Fail | 0 |
+| 1 | Pass | 60 |
+| 2 | Excel | 100 |
+| N/A | Not applicable | Excluded |
+
+### Aggregation
+
+1. **Level-3 → Level-2**: Average all non-N/A Level-3 scores within a Level-2 category
+2. **Level-2 → Level-1**: Average all Level-2 scores within a Level-1 dimension
+3. **Level-1 → Total**: Average all Level-1 dimension scores
+
+## Human Agreement
+
+We validate the judge model against human expert rankings by computing Spearman rank correlation ($\rho$) between the model's rankings and human expert rankings across the five L1 pillars and overall. All correlations are statistically significant ($p < 10^{-4}$, $N = 18$ models).
+
+| Dimension            | Spearman $\rho$ |
+|----------------------|:---------------:|
+| Quality              | 0.89            |
+| Aesthetics           | 0.89            |
+| Alignment            | 0.89            |
+| Real-world Fidelity  | 0.92            |
+| Creative Generation  | 0.92            |
+| **Overall**          | **0.92**        |
+
+## Quick Start
+
+### Get the Inference Code
+
+```bash
+git clone https://github.com/QwenLM/Qwen-Image-Bench.git
+cd Qwen-Image-Bench
+```
+
+### Installation
+
+**1. Create and activate a virtual environment with uv:**
+
+```bash
+uv venv myenv --python 3.11
+source myenv/bin/activate
+```
+
+**2. Install PyTorch** (select the command matching your CUDA version):
+
+See the official guide: [https://pytorch.org/get-started/locally/](https://pytorch.org/get-started/locally/)
+
+**3. Install Python dependencies:**
+
+```bash
+uv pip install -r requirements.txt
+```
+
+This installs all required dependencies including ms-swift.
+
+### Run Inference
+
+```bash
+python judge.py \
+  --input your_data.jsonl \
+  --model Qwen/Qwen-Image-Bench
+```
+
+### Input Format
+
+Prepare a CSV, JSON, or JSONL file with the following columns:
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `ID` | int | Prompt identifier (1-1000), must match benchmark metadata |
+| `prompt` | str | The text prompt used to generate the image |
+| `image_path` | str | Path to the generated image file |
+
+### Output Format
+
+The model outputs a JSON object per dimension, structured as:
+
+```json
+{
+  "Level-2 Dimension": {
+    "Level-3 Dimension": {"score": 0|1|2|"N/A"}
+  }
+}
+```
+
+Example (Quality dimension):
+
+```json
+{
+  "Realism": {
+    "Physical Logic": {"score": 1},
+    "Material Texture": {"score": 2}
+  },
+  "Detail": {
+    "Noise": {"score": 1},
+    "Edge Clarity": {"score": 1},
+    "Naturalness": {"score": 1}
+  },
+  "Resolution": {
+    "Resolution": {"score": 2}
+  }
+}
+```
+
+### CLI Options
+
+| Argument | Default | Description |
+|----------|---------|-------------|
+| `--input` | (required) | Input CSV/JSON/JSONL with ID, prompt, image_path |
+| `--model` | (required) | HuggingFace model ID or local model path |
+| `--hf-bench-repo` | - | HF dataset repo for bench metadata |
+| `--local-metadata` | - | Local metadata file path (overrides default) |
+| `--max-batch-size` | 24 | ms-swift max_batch_size |
+| `--max-new-tokens` | 4096 | Max generation tokens |
+
+## Inference Parameters
+
+The judge model uses fixed inference parameters for reproducibility:
+
+| Parameter | Value |
+|-----------|-------|
+| `seed` | 42 |
+| `temperature` | 0 |
+| `top_k` | 1 |
+| `top_p` | 1.0 |
+| `repetition_penalty` | 1.05 |
+| `max_new_tokens` | 4096 |
+| `enable_thinking` | True |
+| `max_batch_size` | 24 |
+
+
+## Citation
+
+If you find this model useful, please cite our paper:
+
+```bibtex
+@article{TODO,
+  title={TODO},
+  author={TODO},
+  journal={TODO},
+  year={TODO}
+}
+```
+
+## License
+
+This project is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).

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 (preserve_thinking is defined and preserve_thinking is true) or (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 | string if args_value is string else args_value | tojson | safe %}
+                        {{- 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 +1,147 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 248046,
+  "hidden_size": 5120,
+  "image_token_id": 248056,
+  "language_model_only": false,
+  "model_type": "qwen3_5",
+  "pad_token_id": 248044,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": 248044,
+    "dtype": "bfloat16",
+    "eos_token_id": 248044,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 5120,
+    "initializer_range": 0.02,
+    "intermediate_size": 17408,
+    "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_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": 48,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 262144,
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 24,
+    "num_hidden_layers": 64,
+    "num_key_value_heads": 4,
+    "output_gate_type": "swish",
+    "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": false,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.2.0",
+  "use_cache": false,
+  "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": 5120,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 248054,
+  "vision_start_token_id": 248053
+}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "bos_token_id": 248044,
+  "do_sample": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248044,
+  "temperature": 1.0,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.2.0"
+}

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preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "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",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

processor_config.json

@@ -0,0 +1,63 @@
+{
+  "image_processor": {
+    "data_format": "channels_first",
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "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
+    ],
+    "merge_size": 2,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "size": {
+      "longest_edge": 16777216,
+      "shortest_edge": 65536
+    },
+    "temporal_patch_size": 2
+  },
+  "processor_class": "Qwen3VLProcessor",
+  "video_processor": {
+    "data_format": "channels_first",
+    "default_to_square": true,
+    "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
+    ],
+    "max_frames": 768,
+    "merge_size": 2,
+    "min_frames": 4,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "size": {
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+      "shortest_edge": 4096
+    },
+    "temporal_patch_size": 2,
+    "video_processor_type": "Qwen3VLVideoProcessor"
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4
+size 19989343

tokenizer_config.json

@@ -0,0 +1,32 @@
+{
+  "add_prefix_space": false,
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "image_token": "<|image_pad|>",
+  "is_local": true,
+  "model_max_length": 262144,
+  "model_specific_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|>"
+  },
+  "pad_token": "<|endoftext|>",
+  "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+",
+  "processor_class": "Qwen3VLProcessor",
+  "split_special_tokens": false,
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>"
+}