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text_encoder/.gitattributes +36 -0
text_encoder/README.md +117 -0
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vae/diffusion_pytorch_model.safetensors +3 -0

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+---
+license: apache-2.0
+language:
+- en
+- zh
+library_name: diffusers
+pipeline_tag: text-to-image
+---
+<p align="center">
+    <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/qwen_image_logo.png" width="400"/>
+<p>
+<p align="center">
+          💜 <a href="https://chat.qwen.ai/"><b>Qwen Chat</b></a>&nbsp&nbsp | &nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen/Qwen-Image">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/models/Qwen/Qwen-Image">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf">Tech Report</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image/">Blog</a> &nbsp&nbsp
+<br>
+🖥️ <a href="https://huggingface.co/spaces/Qwen/qwen-image">Demo</a>&nbsp&nbsp | &nbsp&nbsp💬 <a href="https://github.com/QwenLM/Qwen-Image/blob/main/assets/wechat.png">WeChat (微信)</a>&nbsp&nbsp | &nbsp&nbsp🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>&nbsp&nbsp
+</p>
+<p align="center">
+    <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/merge3.jpg" width="1600"/>
+<p>
+## Introduction
+We are thrilled to release **Qwen-Image**, an image generation foundation model in the Qwen series that achieves significant advances in **complex text rendering** and **precise image editing**. Experiments show strong general capabilities in both image generation and editing, with exceptional performance in text rendering, especially for Chinese.
+![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/bench.png#center)
+## News
+- 2025.08.04: We released the [Technical Report](https://arxiv.org/abs/2508.02324) of Qwen-Image!
+- 2025.08.04: We released Qwen-Image weights! Check at [huggingface](https://huggingface.co/Qwen/Qwen-Image) and [Modelscope](https://modelscope.cn/models/Qwen/Qwen-Image)!
+- 2025.08.04: We released Qwen-Image! Check our [blog](https://qwenlm.github.io/blog/qwen-image) for more details!
+## Quick Start
+Install the latest version of diffusers
+```
+pip install git+https://github.com/huggingface/diffusers
+```
+The following contains a code snippet illustrating how to use the model to generate images based on text prompts:
+```python
+from diffusers import DiffusionPipeline
+import torch
+model_name = "Qwen/Qwen-Image"
+# Load the pipeline
+if torch.cuda.is_available():
+    torch_dtype = torch.bfloat16
+    device = "cuda"
+else:
+    torch_dtype = torch.float32
+    device = "cpu"
+pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
+pipe = pipe.to(device)
+positive_magic = {
+    "en": ", Ultra HD, 4K, cinematic composition.", # for english prompt
+    "zh": ", 超清，4K，电影级构图." # for chinese prompt
+}
+# Generate image
+prompt = '''A coffee shop entrance features a chalkboard sign reading "Qwen Coffee 😊 $2 per cup," with a neon light beside it displaying "通义千问". Next to it hangs a poster showing a beautiful Chinese woman, and beneath the poster is written "π≈3.1415926-53589793-23846264-33832795-02384197". Ultra HD, 4K, cinematic composition'''
+negative_prompt = " " # using an empty string if you do not have specific concept to remove
+# Generate with different aspect ratios
+aspect_ratios = {
+    "1:1": (1328, 1328),
+    "16:9": (1664, 928),
+    "9:16": (928, 1664),
+    "4:3": (1472, 1140),
+    "3:4": (1140, 1472),
+    "3:2": (1584, 1056),
+    "2:3": (1056, 1584),
+}
+width, height = aspect_ratios["16:9"]
+image = pipe(
+    prompt=prompt + positive_magic["en"],
+    negative_prompt=negative_prompt,
+    width=width,
+    height=height,
+    num_inference_steps=50,
+    true_cfg_scale=4.0,
+    generator=torch.Generator(device="cuda").manual_seed(42)
+).images[0]
+image.save("example.png")
+```
+## Show Cases
+One of its standout capabilities is high-fidelity text rendering across diverse images. Whether it’s alphabetic languages like English or logographic scripts like Chinese, Qwen-Image preserves typographic details, layout coherence, and contextual harmony with stunning accuracy. Text isn’t just overlaid—it’s seamlessly integrated into the visual fabric.
+![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/s1.jpg#center)
+Beyond text, Qwen-Image excels at general image generation with support for a wide range of artistic styles. From photorealistic scenes to impressionist paintings, from anime aesthetics to minimalist design, the model adapts fluidly to creative prompts, making it a versatile tool for artists, designers, and storytellers.
+![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/s2.jpg#center)
+When it comes to image editing, Qwen-Image goes far beyond simple adjustments. It enables advanced operations such as style transfer, object insertion or removal, detail enhancement, text editing within images, and even human pose manipulation—all with intuitive input and coherent output. This level of control brings professional-grade editing within reach of everyday users.
+![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/s3.jpg#center)
+But Qwen-Image doesn’t just create or edit—it understands. It supports a suite of image understanding tasks, including object detection, semantic segmentation, depth and edge (Canny) estimation, novel view synthesis, and super-resolution. These capabilities, while technically distinct, can all be seen as specialized forms of intelligent image editing, powered by deep visual comprehension.
+![](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/s4.jpg#center)
+Together, these features make Qwen-Image not just a tool for generating pretty pictures, but a comprehensive foundation model for intelligent visual creation and manipulation—where language, layout, and imagery converge.
+## License Agreement
+Qwen-Image is licensed under Apache 2.0.
+## Citation
+We kindly encourage citation of our work if you find it useful.
+```bibtex
+@misc{wu2025qwenimagetechnicalreport,
+      title={Qwen-Image Technical Report},
+      author={Chenfei Wu and Jiahao Li and Jingren Zhou and Junyang Lin and Kaiyuan Gao and Kun Yan and Sheng-ming Yin and Shuai Bai and Xiao Xu and Yilei Chen and Yuxiang Chen and Zecheng Tang and Zekai Zhang and Zhengyi Wang and An Yang and Bowen Yu and Chen Cheng and Dayiheng Liu and Deqing Li and Hang Zhang and Hao Meng and Hu Wei and Jingyuan Ni and Kai Chen and Kuan Cao and Liang Peng and Lin Qu and Minggang Wu and Peng Wang and Shuting Yu and Tingkun Wen and Wensen Feng and Xiaoxiao Xu and Yi Wang and Yichang Zhang and Yongqiang Zhu and Yujia Wu and Yuxuan Cai and Zenan Liu},
+      year={2025},
+      eprint={2508.02324},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2508.02324},
+}
+```

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+{
+  "_class_name": "QwenImagePipeline",
+  "_diffusers_version": "0.34.0.dev0",
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "Qwen2_5_VLForConditionalGeneration"
+  ],
+  "tokenizer": [
+    "transformers",
+    "Qwen2Tokenizer"
+  ],
+  "transformer": [
+    "diffusers",
+    "QwenImageTransformer2DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKLQwenImage"
+  ]
+}

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+{
+  "_class_name": "FlowMatchEulerDiscreteScheduler",
+  "_diffusers_version": "0.34.0.dev0",
+  "base_image_seq_len": 256,
+  "base_shift": 0.5,
+  "invert_sigmas": false,
+  "max_image_seq_len": 8192,
+  "max_shift": 0.9,
+  "num_train_timesteps": 1000,
+  "shift": 1.0,
+  "shift_terminal": 0.02,
+  "stochastic_sampling": false,
+  "time_shift_type": "exponential",
+  "use_beta_sigmas": false,
+  "use_dynamic_shifting": true,
+  "use_exponential_sigmas": false,
+  "use_karras_sigmas": false
+}

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+---
+license: apache-2.0
+language:
+- zh
+- en
+tags:
+- qwen
+- qwen2.5-vl
+- image-captioning
+- multimodal
+- nsfw
+- long-caption
+library_name: transformers
+base_model:
+- Qwen/Qwen2.5-VL-7B-Instruct
+- XiaomiMiMo/MiMo-VL-7B-RL-2508
+---
+# 模型名称：thesby/Qwen2.5-VL-7B-NSFW-Caption-V4
+## 模型简介 (Model Description)
+**thesby/Qwen2.5-VL-7B-NSFW-Caption-V4** 是一个专为高质量图像描述（Image Captioning）而优化的多模态大模型。该模型基于强大的 `Qwen/Qwen2.5-VL-7B-Instruct` 进行Lora微调，旨在提供卓越的图像理解和描述生成能力。
+我们在一个包含约 **200 万** 高质量图文对的混合数据集上对模型进行了训练，使其在多个维度上都表现出色。相比于 V3，V4模型加入了更多 NSFW 数据和人工标注数据。
+### 主要特点 (Key Features)
+1.  **超高质量的图片描述能力 (Ultra-High Quality Captions)**：
+    模型能够精准捕捉图像中的核心主体、环境背景、人物情绪、物体材质和光影等丰富细节，描述能力超过 gpt4.1-mini，接近于 gemini-2.5-flash。
+2.  **SFW & NSFW 内容全覆盖 (Support for both SFW & NSFW Content)**：
+    经过特殊的数据集训练，模型能够有效识别并描述 SFW (Safe for Work) 和 NSFW (Not Safe for Work) 类型的图像内容。无论是日常生活场景还是成人向内容，都能生成恰当且信息丰富的描述，极大地拓宽了模型的适用边界。
+3.  **超长文本描述能力 (Long-form Detailed Description)**：
+    与传统模型生成简短标题不同，本模型擅长对复杂的图像场景进行详尽入微的描绘。它可以生成包含数百个单词的详细段落，深入分析图像的叙事结构和潜在含义，尤其适合需要深度内容解读的应用场景。
+## 如何使用 (How to Use)
+使用方式和 Qwen/Qwen2.5-VL-7B-Instruct 完全相同，模型在图片最大尺寸 800*800 微调，遵从这一限制可以获得更好的效果。
+```python
+from transformers import Qwen2_5_VLForConditionalGeneration, AutoTokenizer, AutoProcessor
+from qwen_vl_utils import process_vision_info
+# default: Load the model on the available device(s)
+model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
+    "thesby/Qwen2.5-VL-7B-NSFW-Caption-V4", torch_dtype="auto", device_map="auto"
+)
+# default processer
+processor = AutoProcessor.from_pretrained("thesby/Qwen2.5-VL-7B-NSFW-Caption-V4")
+# The default range for the number of visual tokens per image in the model is 4-16384.
+# You can set min_pixels and max_pixels according to your needs, such as a token range of 256-1280, to balance performance and cost.
+# min_pixels = 256*28*28
+# max_pixels = 800 * 800
+# processor = AutoProcessor.from_pretrained("thesby/Qwen2.5-VL-7B-NSFW-Caption-V4", min_pixels=min_pixels, max_pixels=max_pixels)
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "image",
+                "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
+            },
+            {"type": "text", "text": "请用自然流畅的中文对以下图片进行全面而详细的描述。包括所有可见元素及其属性（如颜色、大小、形状、质地），它们的空间关系，以及任何显著特征或上下文。确保用自然流畅的中文描述清晰、生动，能够捕捉图片的每一个方面，不遗漏任何重要细节。"},
+        ],
+    }
+]
+# Preparation for inference
+text = processor.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True
+)
+image_inputs, video_inputs = process_vision_info(messages)
+inputs = processor(
+    text=[text],
+    images=image_inputs,
+    videos=video_inputs,
+    padding=True,
+    return_tensors="pt",
+)
+inputs = inputs.to("cuda")
+# Inference: Generation of the output
+generated_ids = model.generate(**inputs, max_new_tokens=128)
+generated_ids_trimmed = [
+    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
+]
+output_text = processor.batch_decode(
+    generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+)
+print(output_text)
+```
+## 用途与限制 (Uses and Limitations)
+### 预期用途 (Intended Uses)
+*   **自动化内容标注**：为海量图片生成高质量的描述和标签，用于内容管理、检索和推荐系统。
+*   **无障碍辅助功能**：为视障用户描述图像内容，帮助他们理解视觉信息。
+*   **创意内容生成**：作为灵感来源，为艺术创作、故事写作、广告文案等提供基于图像的文本描述。
+*   **数字内容分析**：对包括SFW和NSFW在内的多种图像内容进行自动化分析和归档。
+### 不适用范围 (Out-of-Scope)
+*   本模型不应用于生成任何有害、非法、歧视性或侵犯他人隐私的内容。
+*   模型的输出不应被视为绝对事实，更不能用于任何需要高精度和高可靠性的关键决策（如医疗诊断、法律判决等），所有重要应用都需有人工审核。
+*   用户在使用模型处理NSFW内容时，应严格遵守当地法律法规，并承担相应责任。
+### 局限性与偏见 (Limitations and Bias)
+*   **幻觉 (Hallucination)**：与所有大模型一样，本模型可能产生“幻觉”，即生成图像中不存在的细节。
+*   **数据偏见 (Data Bias)**：模型的输出可能反映其训练数据中存在的社会和文化偏见（例如，在性别、种族或年龄方面的刻板印象）。
+*   **NSFW判断边界**：对于处于SFW和NSFW边界的模糊图像，模型的判断和描述可能与人类预期不符。
+## 训练细节 (Training Details)
+### 训练数据 (Training Data)
+本模型在一个精心构建的、约 **200 万** 图文对的数据集上进行了微调。该数据集经过严格的筛选和清洗，混合了：
+*   高质量的公开图文数据集。
+*   专门收集和标注的、涵盖广泛SFW和NSFW场景的私有数据集。
+数据分布旨在提升模型在细节捕捉和长文本生成方面的能力，同时确保对不同类型内容的泛化性。
+### 训练过程 (Training Procedure)
+*   **基础模型 (Base Model)**：`Qwen/Qwen2.5-VL-7B-Instruct`
+*   **微调策略 (Finetuning Strategy)**：Lora微调 (Lora Fine-tuning)
+*   **框架 (Framework)**：unsloth
+*   **主要超参数 (Hyperparameters)**：
+    *   Learning Rate: 2e-5
+    *   Batch Size: 16
+    *   Epochs: 1
+    *   Optimizer: AdamW
+### 计划 (Plans)
+*   提高**英文**caption效果
+*   增加**短视频**caption能力

text_encoder/added_tokens.json ADDED Viewed

	@@ -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
+}

text_encoder/chat_template.jinja ADDED Viewed

	@@ -0,0 +1,7 @@

+{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system
+You are MiMo, an AI assistant developed by Xiaomi.<|im_end|>
+{% endif %}<|im_start|>{{ message['role'] }}
+{% if message['content'] is string %}{{ message['content'] }}<|im_end|>
+{% 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 %}<|im_end|>
+{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant
+{% endif %}

text_encoder/config.json ADDED Viewed

	@@ -0,0 +1,147 @@

+{
+  "architectures": [
+    "Qwen2_5_VLForConditionalGeneration"
+  ],
+  "attention_bias": true,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "image_token_id": 151655,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 128000,
+  "max_window_layers": 32,
+  "model_type": "qwen2_5_vl",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151643,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "mrope_section": [
+      16,
+      24,
+      24
+    ],
+    "rope_type": "default",
+    "type": "default"
+  },
+  "rope_theta": 640000.0,
+  "sliding_window": 8192,
+  "text_config": {
+    "architectures": [
+      "Qwen2_5_VLForConditionalGeneration"
+    ],
+    "attention_bias": true,
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "eos_token_id": 151645,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "image_token_id": null,
+    "initializer_range": 0.02,
+    "intermediate_size": 11008,
+    "layer_types": [
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention",
+      "full_attention"
+    ],
+    "max_position_embeddings": 128000,
+    "max_window_layers": 32,
+    "model_type": "qwen2_5_vl_text",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 36,
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": {
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+      "rope_type": "default",
+      "type": "default"
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+    "sliding_window": null,
+    "torch_dtype": "bfloat16",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "video_token_id": null,
+    "vision_end_token_id": 151653,
+    "vision_start_token_id": 151652,
+    "vision_token_id": 151654,
+    "vocab_size": 151680
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+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.55.4",
+  "unsloth_version": "2025.9.6",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "video_token_id": 151656,
+  "vision_config": {
+    "depth": 32,
+    "fullatt_block_indexes": [
+      7,
+      15,
+      23,
+      31
+    ],
+    "hidden_act": "silu",
+    "hidden_size": 1280,
+    "in_channels": 3,
+    "in_chans": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 3456,
+    "model_type": "qwen2_5_vl",
+    "num_heads": 16,
+    "out_hidden_size": 4096,
+    "patch_size": 14,
+    "spatial_merge_size": 2,
+    "spatial_patch_size": 14,
+    "temporal_patch_size": 2,
+    "tokens_per_second": 2,
+    "torch_dtype": "bfloat16",
+    "window_size": 112
+  },
+  "vision_end_token_id": 151653,
+  "vision_start_token_id": 151652,
+  "vision_token_id": 151654,
+  "vocab_size": 151680
+}

text_encoder/generation_config.json ADDED Viewed

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+  "do_sample": true,
+  "eos_token_id": [
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+  "temperature": 0.1,
+  "top_k": 1,
+  "top_p": 0.001,
+  "transformers_version": "4.53.1"
+}

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+  }
+}

text_encoder/preprocessor_config.json ADDED Viewed

	@@ -0,0 +1,37 @@

+{
+  "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_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "Qwen2VLImageProcessorFast",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "input_data_format": null,
+  "max_pixels": 12845056,
+  "merge_size": 2,
+  "min_pixels": 3136,
+  "patch_size": 14,
+  "processor_class": "Qwen2_5_VLProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "return_tensors": null,
+  "size": {
+    "longest_edge": 12845056,
+    "shortest_edge": 3136
+  },
+  "temporal_patch_size": 2
+}

text_encoder/special_tokens_map.json ADDED Viewed

	@@ -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
+  }
+}

text_encoder/tokenizer.json ADDED Viewed

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0e9ff5e369d57eba6483d24fda0078f2f6f59f718cf93352ce17bd48c1dbbdc0
+size 11421995

text_encoder/tokenizer_config.json ADDED Viewed

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
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+      "rstrip": false,
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+    "151658": {
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+    },
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+    },
+    "151664": {
+      "content": "<|file_sep|>",
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+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
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+    "<|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": {},
+  "max_length": 5120,
+  "model_max_length": 131072,
+  "pad_to_multiple_of": null,
+  "pad_token": "<|endoftext|>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "processor_class": "Qwen2_5_VLProcessor",
+  "split_special_tokens": false,
+  "stride": 0,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": null
+}

text_encoder/video_preprocessor_config.json ADDED Viewed

	@@ -0,0 +1,43 @@

+{
+  "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_pad": null,
+  "do_rescale": true,
+  "do_resize": true,
+  "do_sample_frames": false,
+  "fps": null,
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "input_data_format": null,
+  "max_frames": 768,
+  "max_pixels": 12845056,
+  "merge_size": 2,
+  "min_frames": 4,
+  "min_pixels": 3136,
+  "num_frames": null,
+  "patch_size": 14,
+  "processor_class": "Qwen2_5_VLProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "longest_edge": 12845056,
+    "shortest_edge": 3136
+  },
+  "size_divisor": null,
+  "temporal_patch_size": 2,
+  "video_metadata": null,
+  "video_processor_type": "Qwen2VLVideoProcessor"
+}

text_encoder/vocab.json ADDED Viewed

The diff for this file is too large to render. See raw diff

tokenizer/added_tokens.json ADDED Viewed

	@@ -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
+}

tokenizer/chat_template.jinja ADDED Viewed

	@@ -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 %}

tokenizer/merges.txt ADDED Viewed

The diff for this file is too large to render. See raw diff

tokenizer/special_tokens_map.json ADDED Viewed

	@@ -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
+  }
+}

tokenizer/tokenizer_config.json ADDED Viewed

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+{
+  "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
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