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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ 2B/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ 4B/tokenizer.json filter=lfs diff=lfs merge=lfs -text
2B/LICENSE ADDED
@@ -0,0 +1,435 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ Tencent is pleased to support the open source community by making WeVisOne-VL-2B available.
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+ Copyright (C) 2026 Tencent. All rights reserved.
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+ The open-source software and/or models included in this distribution may have been modified by Tencent (“Tencent Modifications”). All Tencent Modifications are Copyright (C) Tencent.
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+ WeVisOne-VL-2B is licensed under Apache-2.0, except for the third-party components listed below, which remain licensed under their respective original terms. WeVisOne-VL-2B does not impose any additional restrictions beyond those specified in the original licenses of these third-party components. Users are required to comply with all applicable terms and conditions of the original licenses and to ensure that the use of these third-party components conforms to all relevant laws and regulations.
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+ For the avoidance of doubt, WeVisOne-VL-2B refers to code, parameters, and weights made publicly available by Tencent in accordance with Apache-2.0.
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+ Terms of Apache-2.0:
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+ --------------------------------------------------------------------
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+ This open-source project, WeVisOne-VL-2B, builds upon the following open-source models and/or software components, each of which remains licensed under its original license. Certain models or software may include modifications made by Tencent (“Tencent Modifications”), which are Copyright (C) Tencent.
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+ Open Source Model Licensed under the Apache-2.0:
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+ 1. Qwen3-VL-2B-Instruct
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+ Please note this model has been modified by Tencent in this distribution.
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+ Terms of the Apache-2.0:
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+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+ 1. Definitions.
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+ END OF TERMS AND CONDITIONS
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+ APPENDIX: How to apply the Apache License to your work.
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+ To apply the Apache License to your work, attach the following
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+
2B/README.md ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ pipeline_tag: image-text-to-text
4
+ library_name: transformers
5
+ tags:
6
+ - vision-language
7
+ - object-detection
8
+ - referring-expression-comprehension
9
+ - object-counting
10
+ - point-grounding
11
+ - ocr
12
+ - referring-expression-segmentation
13
+ - image-matting
14
+ ---
15
+
16
+ # WeVisOne-VL: Unified Visual Perception from Objects to Pixels
17
+
18
+ **Paper:** [WeVisOne-VL: Unified Visual Perception from Objects to Pixels](https://huggingface.co/papers/2610.31329) | **Project Page:** [WeVisOne-VL](https://tencent.github.io/WeVisOne-VL)
19
+
20
+ **WeVisOne-VL** (**We**Chat **Vis**ion All-in-**One**) is a unified vision-language model developed by WeChat Vision, Tencent Inc. Built upon Qwen3-VL, it unifies object-level perception (open-vocabulary object detection, referring localization, object counting, object pointing, and OCR) and pixel-level perception (referring segmentation and promptable alpha matting) through structured next-token prediction and a lightweight 9.6M-parameter pixel decoder.
21
+
22
+ ## Quick Start
23
+
24
+ Install the inference package from [GitHub](https://github.com/Tencent/WeVisOne-VL), then:
25
+
26
+ ```python
27
+ from PIL import Image
28
+ from wevisone_vl import WeVisOneVL
29
+
30
+ model = WeVisOneVL("tencent/WeVisOne-VL-2B", device="auto", dtype="bfloat16")
31
+ image = Image.open("example.jpg").convert("RGB")
32
+ result = model.predict(image, task="matting", query="person", temperature=0.0)
33
+ print(result.response, len(result.masks))
34
+ ```
35
+
36
+ ## Architecture & Released Revision
37
+
38
+ The model uses dedicated coordinate tokens (`<0>` ... `<1000>`) to represent normalized bounding boxes and points, returns `None` when a queried target is absent, and emits a special instance token (`<OBJ>`, token ID `152678`) after each predicted box for dense tasks.
39
+
40
+ The attached `mask_decoder.pt` (9,609,764 parameters) is a required core component that combines:
41
+ - A **Visual Feature Adapter** over multi-level Qwen3-VL pre-merging ViT features;
42
+ - A **Box-Guided Query Decoder** with 6 deformable cross-attention blocks initialized from the `<OBJ>` hidden state and Fourier-encoded box prior;
43
+ - An **Instance-Conditioned Dense Prediction Head** with `FullCanvasAlphaCascadeHead` (refining predictions across S/4, S/2, and S/1 to output full-resolution continuous alpha mattes at stride 1).
44
+
45
+ ## Intended Use
46
+
47
+ The release is intended for research in visual grounding, referring localization, pointing, counting, OCR localization, referring segmentation, and image matting. It is not intended to make autonomous high-impact decisions or to identify individuals.
48
+
49
+ ## Limitations
50
+
51
+ - Fine alpha boundaries remain sensitive to image resolution, severe occlusion, complex transparency, and prompt phrasing.
52
+ - For inference efficiency, the model directly generates structured outputs without explicit chain-of-thought (CoT) reasoning, and currently targets single-turn image perception (video grids are rejected by the pixel decoder).
53
+
54
+ ## License
55
+
56
+ Unless otherwise noted, Tencent-authored code in this repository is released under the [Apache License 2.0](LICENSE).
57
+
58
+ Third-party components retain their original licenses and copyright notices. Please review the corresponding source files before use.
59
+
60
+ ## Citation
61
+
62
+ If WeVisOne-VL is helpful to your work, please consider giving us a ⭐ and citing:
63
+
64
+ ```bibtex
65
+ @article{liang2026wevisone,
66
+ title={WeVisOne-VL: Unified Visual Perception from Objects to Pixels},
67
+ author={Liang, Tianming and Pan, Junyi and Li, Yuxi and Fu, Canmiao and Huang, Zhipeng and Sun, Chong and Li, Chen and Lyu, Jing},
68
+ journal={arXiv preprint arXiv:2610.31329},
69
+ year={2026}
70
+ }
71
+ ```
2B/chat_template.jinja ADDED
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1
+ {%- if tools %}
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+ {{- '<|im_start|>system\n' }}
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+ {%- if messages[0].role == 'system' %}
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+ {%- if messages[0].content is string %}
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+ {{- messages[0].content }}
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+ {%- else %}
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+ {%- for content in messages[0].content %}
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+ {%- if 'text' in content %}
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+ {{- content.text }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '\n\n' }}
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+ {%- endif %}
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+ {{- "# 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>" }}
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+ {%- for tool in tools %}
17
+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- endfor %}
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+ {{- "\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" }}
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+ {%- else %}
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+ {%- if messages[0].role == 'system' %}
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+ {{- '<|im_start|>system\n' }}
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+ {%- if messages[0].content is string %}
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+ {{- messages[0].content }}
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+ {%- else %}
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+ {%- for content in messages[0].content %}
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+ {%- if 'text' in content %}
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+ {{- content.text }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- set image_count = namespace(value=0) %}
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+ {%- set video_count = namespace(value=0) %}
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+ {%- for message in messages %}
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+ {%- if message.role == "user" %}
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+ {{- '<|im_start|>' + message.role + '\n' }}
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+ {%- if message.content is string %}
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+ {{- message.content }}
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+ {%- else %}
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+ {%- for content in message.content %}
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+ {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
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+ {%- set image_count.value = image_count.value + 1 %}
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+ {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
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+ <|vision_start|><|image_pad|><|vision_end|>
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+ {%- elif content.type == 'video' or 'video' in content %}
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+ {%- set video_count.value = video_count.value + 1 %}
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+ {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
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+ <|vision_start|><|video_pad|><|vision_end|>
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+ {%- elif 'text' in content %}
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+ {{- content.text }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif message.role == "assistant" %}
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+ {{- '<|im_start|>' + message.role + '\n' }}
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+ {%- if message.content is string %}
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+ {{- message.content }}
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+ {%- else %}
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+ {%- for content_item in message.content %}
65
+ {%- if 'text' in content_item %}
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+ {{- content_item.text }}
67
+ {%- endif %}
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+ {%- endfor %}
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+ {%- endif %}
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+ {%- if message.tool_calls %}
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+ {%- for tool_call in message.tool_calls %}
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+ {%- if (loop.first and message.content) or (not loop.first) %}
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+ {{- '\n' }}
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+ {%- endif %}
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+ {%- if tool_call.function %}
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+ {%- set tool_call = tool_call.function %}
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+ {%- endif %}
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+ {{- '<tool_call>\n{"name": "' }}
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+ {{- tool_call.name }}
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+ {{- '", "arguments": ' }}
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+ {%- if tool_call.arguments is string %}
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+ {{- tool_call.arguments }}
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+ {%- else %}
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+ {{- tool_call.arguments | tojson }}
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+ {%- endif %}
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+ {{- '}\n</tool_call>' }}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif message.role == "tool" %}
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+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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+ {{- '<|im_start|>user' }}
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+ {%- endif %}
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+ {{- '\n<tool_response>\n' }}
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+ {%- if message.content is string %}
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+ {{- message.content }}
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+ {%- else %}
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+ {%- for content in message.content %}
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+ {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
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+ {%- set image_count.value = image_count.value + 1 %}
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+ {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
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+ <|vision_start|><|image_pad|><|vision_end|>
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+ {%- elif content.type == 'video' or 'video' in content %}
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+ {%- set video_count.value = video_count.value + 1 %}
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+ {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
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+ <|vision_start|><|video_pad|><|vision_end|>
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+ {%- elif 'text' in content %}
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+ {{- content.text }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '\n</tool_response>' }}
113
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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+ {{- '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- if add_generation_prompt %}
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+ {{- '<|im_start|>assistant\n' }}
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+ {%- endif %}
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+ "temperature": 0.7,
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+ "top_k": 20,
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+ "top_p": 0.8,
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+ "transformers_version": "5.5.3"
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4B/LICENSE ADDED
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1
+ Tencent is pleased to support the open source community by making WeVisOne-VL-4B available.
2
+
3
+ Copyright (C) 2026 Tencent. All rights reserved.
4
+
5
+ The open-source software and/or models included in this distribution may have been modified by Tencent (“Tencent Modifications”). All Tencent Modifications are Copyright (C) Tencent.
6
+
7
+ WeVisOne-VL-4B is licensed under Apache-2.0, except for the third-party components listed below, which remain licensed under their respective original terms. WeVisOne-VL-4B does not impose any additional restrictions beyond those specified in the original licenses of these third-party components. Users are required to comply with all applicable terms and conditions of the original licenses and to ensure that the use of these third-party components conforms to all relevant laws and regulations.
8
+
9
+ For the avoidance of doubt, WeVisOne-VL-4B refers to code, parameters, and weights made publicly available by Tencent in accordance with Apache-2.0.
10
+
11
+ Terms of Apache-2.0:
12
+ --------------------------------------------------------------------
13
+ Apache License
14
+ Version 2.0, January 2004
15
+ http://www.apache.org/licenses/
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+
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+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+
4B/README.md ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ pipeline_tag: image-text-to-text
4
+ library_name: transformers
5
+ tags:
6
+ - vision-language
7
+ - object-detection
8
+ - referring-expression-comprehension
9
+ - object-counting
10
+ - point-grounding
11
+ - ocr
12
+ - referring-expression-segmentation
13
+ - image-matting
14
+ ---
15
+
16
+ # WeVisOne-VL: Unified Visual Perception from Objects to Pixels
17
+
18
+ **Paper:** [WeVisOne-VL: Unified Visual Perception from Objects to Pixels](https://huggingface.co/papers/2610.31329) | **Project Page:** [WeVisOne-VL](https://tencent.github.io/WeVisOne-VL)
19
+
20
+ **WeVisOne-VL** (**We**Chat **Vis**ion All-in-**One**) is a unified vision-language model developed by WeChat Vision, Tencent Inc. Built upon Qwen3-VL, it unifies object-level perception (open-vocabulary object detection, referring localization, object counting, object pointing, and OCR) and pixel-level perception (referring segmentation and promptable alpha matting) through structured next-token prediction and a lightweight 9.6M-parameter pixel decoder.
21
+
22
+ ## Quick Start
23
+
24
+ Install the inference package from [GitHub](https://github.com/Tencent/WeVisOne-VL), then:
25
+
26
+ ```python
27
+ from PIL import Image
28
+ from wevisone_vl import WeVisOneVL
29
+
30
+ model = WeVisOneVL("tencent/WeVisOne-VL-4B", device="auto", dtype="bfloat16")
31
+ image = Image.open("example.jpg").convert("RGB")
32
+ result = model.predict(image, task="matting", query="person", temperature=0.0)
33
+ print(result.response, len(result.masks))
34
+ ```
35
+
36
+ ## Architecture & Released Revision
37
+
38
+ The model uses dedicated coordinate tokens (`<0>` ... `<1000>`) to represent normalized bounding boxes and points, returns `None` when a queried target is absent, and emits a special instance token (`<OBJ>`, token ID `152678`) after each predicted box for dense tasks.
39
+
40
+ The attached `mask_decoder.pt` (9,609,764 parameters) is a required core component that combines:
41
+ - A **Visual Feature Adapter** over multi-level Qwen3-VL pre-merging ViT features;
42
+ - A **Box-Guided Query Decoder** with 6 deformable cross-attention blocks initialized from the `<OBJ>` hidden state and Fourier-encoded box prior;
43
+ - An **Instance-Conditioned Dense Prediction Head** with `FullCanvasAlphaCascadeHead` (refining predictions across S/4, S/2, and S/1 to output full-resolution continuous alpha mattes at stride 1).
44
+
45
+ ## Intended Use
46
+
47
+ The release is intended for research in visual grounding, referring localization, pointing, counting, OCR localization, referring segmentation, and image matting. It is not intended to make autonomous high-impact decisions or to identify individuals.
48
+
49
+ ## Limitations
50
+
51
+ - Fine alpha boundaries remain sensitive to image resolution, severe occlusion, complex transparency, and prompt phrasing.
52
+ - For inference efficiency, the model directly generates structured outputs without explicit chain-of-thought (CoT) reasoning, and currently targets single-turn image perception (video grids are rejected by the pixel decoder).
53
+
54
+ ## License
55
+
56
+ Unless otherwise noted, Tencent-authored code in this repository is released under the [Apache License 2.0](LICENSE).
57
+
58
+ Third-party components retain their original licenses and copyright notices. Please review the corresponding source files before use.
59
+
60
+ ## Citation
61
+
62
+ If WeVisOne-VL is helpful to your work, please consider giving us a ⭐ and citing:
63
+
64
+ ```bibtex
65
+ @article{liang2026wevisone,
66
+ title={WeVisOne-VL: Unified Visual Perception from Objects to Pixels},
67
+ author={Liang, Tianming and Pan, Junyi and Li, Yuxi and Fu, Canmiao and Huang, Zhipeng and Sun, Chong and Li, Chen and Lyu, Jing},
68
+ journal={arXiv preprint arXiv:2610.31329},
69
+ year={2026}
70
+ }
71
+ ```
4B/chat_template.jinja ADDED
@@ -0,0 +1,120 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0].role == 'system' %}
4
+ {%- if messages[0].content is string %}
5
+ {{- messages[0].content }}
6
+ {%- else %}
7
+ {%- for content in messages[0].content %}
8
+ {%- if 'text' in content %}
9
+ {{- content.text }}
10
+ {%- endif %}
11
+ {%- endfor %}
12
+ {%- endif %}
13
+ {{- '\n\n' }}
14
+ {%- endif %}
15
+ {{- "# 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>" }}
16
+ {%- for tool in tools %}
17
+ {{- "\n" }}
18
+ {{- tool | tojson }}
19
+ {%- endfor %}
20
+ {{- "\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" }}
21
+ {%- else %}
22
+ {%- if messages[0].role == 'system' %}
23
+ {{- '<|im_start|>system\n' }}
24
+ {%- if messages[0].content is string %}
25
+ {{- messages[0].content }}
26
+ {%- else %}
27
+ {%- for content in messages[0].content %}
28
+ {%- if 'text' in content %}
29
+ {{- content.text }}
30
+ {%- endif %}
31
+ {%- endfor %}
32
+ {%- endif %}
33
+ {{- '<|im_end|>\n' }}
34
+ {%- endif %}
35
+ {%- endif %}
36
+ {%- set image_count = namespace(value=0) %}
37
+ {%- set video_count = namespace(value=0) %}
38
+ {%- for message in messages %}
39
+ {%- if message.role == "user" %}
40
+ {{- '<|im_start|>' + message.role + '\n' }}
41
+ {%- if message.content is string %}
42
+ {{- message.content }}
43
+ {%- else %}
44
+ {%- for content in message.content %}
45
+ {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
46
+ {%- set image_count.value = image_count.value + 1 %}
47
+ {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
48
+ <|vision_start|><|image_pad|><|vision_end|>
49
+ {%- elif content.type == 'video' or 'video' in content %}
50
+ {%- set video_count.value = video_count.value + 1 %}
51
+ {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
52
+ <|vision_start|><|video_pad|><|vision_end|>
53
+ {%- elif 'text' in content %}
54
+ {{- content.text }}
55
+ {%- endif %}
56
+ {%- endfor %}
57
+ {%- endif %}
58
+ {{- '<|im_end|>\n' }}
59
+ {%- elif message.role == "assistant" %}
60
+ {{- '<|im_start|>' + message.role + '\n' }}
61
+ {%- if message.content is string %}
62
+ {{- message.content }}
63
+ {%- else %}
64
+ {%- for content_item in message.content %}
65
+ {%- if 'text' in content_item %}
66
+ {{- content_item.text }}
67
+ {%- endif %}
68
+ {%- endfor %}
69
+ {%- endif %}
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+ {%- if message.tool_calls %}
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+ {%- for tool_call in message.tool_calls %}
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+ {%- if (loop.first and message.content) or (not loop.first) %}
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+ {{- '\n' }}
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+ {%- endif %}
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+ {%- if tool_call.function %}
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+ {%- set tool_call = tool_call.function %}
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+ {%- endif %}
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+ {{- '<tool_call>\n{"name": "' }}
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+ {{- tool_call.name }}
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+ {{- '", "arguments": ' }}
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+ {%- endif %}
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+ {{- '}\n</tool_call>' }}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif message.role == "tool" %}
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+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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+ {%- endif %}
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+ {{- '\n<tool_response>\n' }}
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+ {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
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+ {%- set image_count.value = image_count.value + 1 %}
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+ {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
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+ <|vision_start|><|image_pad|><|vision_end|>
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+ {%- elif content.type == 'video' or 'video' in content %}
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+ {%- set video_count.value = video_count.value + 1 %}
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+ {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
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+ <|vision_start|><|video_pad|><|vision_end|>
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+ {%- elif 'text' in content %}
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+ {{- content.text }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '\n</tool_response>' }}
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+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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+ {{- '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- if add_generation_prompt %}
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+ {{- '<|im_start|>assistant\n' }}
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+ {%- endif %}
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+ "temporal_patch_size": 2
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+ "vision_end_token_id": 151653,
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+ "vision_start_token_id": 151652
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+ }
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+ "top_p": 0.8,
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+ "do_normalize": true,
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+ "video_processor_type": "Qwen3VLVideoProcessor"
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+ }
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+ }
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LICENSE ADDED
@@ -0,0 +1,211 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ Tencent is pleased to support the open source community by making WeVisOne-VL available.
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+ Apache License
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README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ pipeline_tag: image-text-to-text
4
+ tags:
5
+ - comfyui
6
+ - wevisone-vl
7
+ - mask2alpha
8
+ - sam2
9
+ - ocr
10
+ - image-matting
11
+ - segmentation
12
+ base_model:
13
+ - tencent/WeVisOne-VL-2B
14
+ - tencent/WeVisOne-VL-4B
15
+ ---
16
+
17
+ # WeVisOne-VL for ComfyUI · T8
18
+
19
+ [English](README.md) | [简体中文](README.zh-CN.md)
20
+
21
+ Original Tencent WeVisOne-VL checkpoints and Mask2Alpha assets, organized for [ComfyUI-WeVisOne-VL-T8](https://github.com/T8mars/Comfyui-WeVisOne-VL-T8). T8 maintains the ComfyUI integration and this distribution; upstream model authors and licenses are preserved.
22
+
23
+ ## Files
24
+
25
+ | Path | Contents |
26
+ | --- | --- |
27
+ | `2B/` | WeVisOne-VL 2B, tokenizer, processor and required pixel decoder |
28
+ | `4B/` | WeVisOne-VL 4B, tokenizer, processor and required pixel decoder |
29
+ | `sam2.1_hiera_base_plus.pt` | Official SAM2.1 Hiera Base+ checkpoint |
30
+ | `mask2alpha_sam2_bplus.pt` | Tencent Mask2Alpha refinement head |
31
+ | `mask2alpha_head.onnx` | Optional fixed-shape ONNX export of the refinement head |
32
+ | `provenance.json`, `SHA256SUMS` | Source revisions, file sizes and SHA-256 checksums |
33
+
34
+ The pretrained weights are copied unchanged. TensorRT engines are built locally for the target GPU/runtime.
35
+
36
+ ## Use in ComfyUI
37
+
38
+ Install the [node package](https://github.com/T8mars/Comfyui-WeVisOne-VL-T8) and follow its setup instructions. The downloader selects only the requested model size and the shared Mask2Alpha checkpoints.
39
+
40
+ For manual download:
41
+
42
+ ```python
43
+ from huggingface_hub import snapshot_download
44
+
45
+ snapshot_download(
46
+ "t8star/WeVisOne-VL-Comfy",
47
+ local_dir="ComfyUI/models/wevisone",
48
+ allow_patterns=["2B/*", "sam2.1_hiera_base_plus.pt", "mask2alpha_sam2_bplus.pt"],
49
+ )
50
+ ```
51
+
52
+ Set `WEVISONE_MODELS` to that directory, or select the model path in the loader. Replace `2B/*` with `4B/*` for 4B. `mask_decoder.pt` is required for text-guided segmentation and matting.
53
+
54
+ ## Sources and license
55
+
56
+ - [Tencent WeVisOne-VL](https://github.com/Tencent/WeVisOne-VL) · [Mask2Alpha branch](https://github.com/Tencent/WeVisOne-VL/tree/mask2alpha)
57
+ - [Official 2B](https://huggingface.co/tencent/WeVisOne-VL-2B) · [Official 4B](https://huggingface.co/tencent/WeVisOne-VL-4B) · [Meta SAM2](https://github.com/facebookresearch/sam2)
58
+
59
+ Apache-2.0. Original notices are retained in each model directory and `LICENSES/`. Pinned provenance is recorded in `provenance.json`.
60
+
61
+ ## T8 links
62
+
63
+ [Bilibili](https://space.bilibili.com/385085361) · [YouTube](https://www.youtube.com/@T8star-Aix/) · [API](https://api.seedance.nz/sign-up?aff=5f4w) · [Free gallery](https://www.openzhenzhen.com) · [Online AI apps](https://www.runninghub.ai/zh-cn/user-center/1907375370302308353/userPost?inviteCode=rh-v1121) · [ComfyUI pack](https://pan.quark.cn/s/264edb7e36bd) · [Hugging Face](https://huggingface.co/t8star)
README.zh-CN.md ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # WeVisOne-VL for ComfyUI · T8
2
+
3
+ [English](README.md) | [简体中文](README.zh-CN.md)
4
+
5
+ 为 [ComfyUI-WeVisOne-VL-T8](https://github.com/T8mars/Comfyui-WeVisOne-VL-T8) 整理的腾讯 WeVisOne-VL 与 Mask2Alpha 模型分发仓库。T8 负责 ComfyUI 集成与整理,保留原作者署名和许可证。
6
+
7
+ ## 文件
8
+
9
+ | 路径 | 内容 |
10
+ | --- | --- |
11
+ | `2B/`、`4B/` | 对应尺寸的原始权重、分词器、预处理配置及像素解码器 |
12
+ | `sam2.1_hiera_base_plus.pt` | 官方 SAM2.1 Hiera Base+ 权重 |
13
+ | `mask2alpha_sam2_bplus.pt` | 腾讯 Mask2Alpha 细化头 |
14
+ | `mask2alpha_head.onnx` | 可选的固定尺寸细化头 ONNX 导出 |
15
+ | `provenance.json`、`SHA256SUMS` | 来源版本、文件大小与校验值 |
16
+
17
+ 预训练权重保持原样。TensorRT engine 按目标 GPU 和运行环境在本地构建。
18
+
19
+ ## 使用
20
+
21
+ 安装 [ComfyUI 节点](https://github.com/T8mars/Comfyui-WeVisOne-VL-T8),按说明准备独立 worker。下载器仅下载所选尺寸和共用的 Mask2Alpha 权重。
22
+
23
+ 手动下载示例:
24
+
25
+ ```python
26
+ from huggingface_hub import snapshot_download
27
+
28
+ snapshot_download(
29
+ "t8star/WeVisOne-VL-Comfy",
30
+ local_dir="ComfyUI/models/wevisone",
31
+ allow_patterns=["2B/*", "sam2.1_hiera_base_plus.pt", "mask2alpha_sam2_bplus.pt"],
32
+ )
33
+ ```
34
+
35
+ 将 `WEVISONE_MODELS` 指向该目录,或在 loader 中指定路径。4B 使用 `4B/*`。文字分割与抠图需要对应目录内的 `mask_decoder.pt`。
36
+
37
+ ## 来源与许可
38
+
39
+ [腾讯 WeVisOne-VL](https://github.com/Tencent/WeVisOne-VL) · [Mask2Alpha 分支](https://github.com/Tencent/WeVisOne-VL/tree/mask2alpha) · [官方 2B](https://huggingface.co/tencent/WeVisOne-VL-2B) · [官方 4B](https://huggingface.co/tencent/WeVisOne-VL-4B) · [Meta SAM2](https://github.com/facebookresearch/sam2)
40
+
41
+ Apache-2.0。原始许可保留在模型目录与 `LICENSES/`,具体版本和文件校验信息见 `provenance.json`。
42
+
43
+ ## T8 链接
44
+
45
+ [B站](https://space.bilibili.com/385085361) · [YouTube](https://www.youtube.com/@T8star-Aix/) · [API](https://api.seedance.nz/sign-up?aff=5f4w) · [免费画廊](https://www.openzhenzhen.com) · [在线 AI 应用](https://www.runninghub.ai/zh-cn/user-center/1907375370302308353/userPost?inviteCode=rh-v1121) · [ComfyUI 整合包](https://pan.quark.cn/s/264edb7e36bd) · [Hugging Face](https://huggingface.co/t8star)
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