Upload openvino_tokenizer.xml with huggingface_hub
Browse files- openvino_tokenizer.xml +902 -0
openvino_tokenizer.xml
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|
| 384 |
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|
| 385 |
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| 386 |
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| 387 |
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|
| 388 |
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</port>
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| 389 |
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| 390 |
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| 391 |
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|
| 392 |
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| 397 |
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| 398 |
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</layer>
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| 399 |
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<layer id="32" name="StringTensorUnpack_629523" type="StringTensorUnpack" version="extension">
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| 400 |
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<data mode="begins_ends" />
|
| 401 |
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<input>
|
| 402 |
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<port id="0" precision="U8">
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| 403 |
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<dim>14600</dim>
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| 404 |
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</port>
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| 405 |
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| 406 |
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| 410 |
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| 412 |
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| 414 |
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| 415 |
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| 416 |
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| 417 |
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| 418 |
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| 422 |
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</port>
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| 424 |
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| 425 |
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</layer>
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<layer id="34" name="BPETokenizer_629531" type="BPETokenizer" version="extension">
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<data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" cache_capacity="30268" />
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| 514 |
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| 516 |
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| 550 |
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</layer>
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| 572 |
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| 575 |
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| 578 |
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| 579 |
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| 580 |
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| 581 |
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| 583 |
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| 598 |
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| 612 |
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| 614 |
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| 616 |
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| 619 |
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| 621 |
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| 622 |
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| 623 |
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| 625 |
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| 626 |
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| 627 |
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| 628 |
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| 629 |
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| 631 |
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| 632 |
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| 633 |
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| 634 |
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| 637 |
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| 638 |
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|
| 639 |
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| 640 |
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| 641 |
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| 642 |
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| 643 |
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| 645 |
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| 646 |
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| 647 |
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| 648 |
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| 649 |
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| 650 |
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| 652 |
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| 653 |
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| 654 |
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|
| 655 |
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| 656 |
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| 657 |
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| 658 |
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| 659 |
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| 661 |
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| 662 |
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| 664 |
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| 665 |
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| 669 |
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| 670 |
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| 671 |
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| 672 |
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| 673 |
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<dim>-1</dim>
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| 674 |
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| 675 |
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| 676 |
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| 677 |
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| 678 |
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| 679 |
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<dim>-1</dim>
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| 680 |
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| 681 |
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| 682 |
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| 684 |
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| 685 |
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| 686 |
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| 687 |
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| 688 |
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| 689 |
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| 690 |
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| 691 |
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| 693 |
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| 697 |
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| 699 |
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| 700 |
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| 701 |
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| 702 |
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| 703 |
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| 704 |
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| 705 |
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| 706 |
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| 707 |
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| 708 |
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| 709 |
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| 711 |
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| 712 |
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| 714 |
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| 715 |
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| 717 |
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| 718 |
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| 719 |
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| 720 |
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| 721 |
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| 722 |
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| 723 |
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| 724 |
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| 725 |
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| 726 |
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| 727 |
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| 728 |
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| 729 |
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| 730 |
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| 731 |
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| 732 |
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| 733 |
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| 734 |
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| 735 |
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| 736 |
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| 737 |
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| 738 |
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| 739 |
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| 740 |
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| 741 |
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<dim>-1</dim>
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| 742 |
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| 744 |
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| 745 |
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| 746 |
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| 747 |
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| 748 |
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| 749 |
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| 750 |
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| 751 |
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| 753 |
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| 754 |
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| 755 |
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| 756 |
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| 757 |
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| 758 |
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| 759 |
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| 760 |
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| 761 |
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| 762 |
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| 763 |
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| 764 |
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| 765 |
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| 766 |
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| 767 |
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<chat_template value="[gMASK]<sop>{% for item in messages %}{% if item['tools'] is defined %}<|system|> 你是一个名为 GLM-4 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的，你的任务是针对用户的问题和要求提供适当的答复和支持。 # 可用工具{% set tools = item['tools'] %}{% for tool in tools %}{% if tool['type'] == 'function' %} ## {{ tool['function']['name'] }} {{ tool['function'] | tojson(indent=4) }} 在调用上述函数时，请使用 Json 格式表示调用的参数。{% elif tool['type'] == 'python' %} ## python 当你向 `python` 发送包含 Python 代码的消息时，该代码将会在一个有状态的 Jupyter notebook 环境中执行。 `python` 返回代码执行的输出，或在执行 60 秒后返回超时。 `/mnt/data` 将会持久化存储你的文件。在此会话中，`python` 无法访问互联网。不要使用 `python` 进行任何网络请求或者在线 API 调用，这些在线内容的访问将不会成功。{% elif tool['type'] == 'simple_browser' %} ## simple_browser 你可以使用 `simple_browser` 工具。该工具支持以下函数： `search(query: str, recency_days: int)`：使用搜索引擎进行查询并显示结果，可以使用 `recency_days` 参数控制搜索内容的时效性。 `mclick(ids: list[int])`：获取一系列指定 id 的页面内容。每次调用时，须选择3-10个页面。选择多个角度的页面，同时尽可能选择可信任的信息来源。考虑到部分页面是无法加载的，你也可以多打开一些可能有用的页面而不用担心内容过多。 `open_url(url: str)`：打开指定的 URL。 使用 `【{引用 id}†{引用文本}】` 来引用内容。 操作步骤：1. 使用 `search` 来获得信息列表; 2. 使用 `mclick` 来获取指定 ID 页面的内容; 3. 根据获得的内容进行回复。在回复中应当引用信息来源。 如果用户提供了 URL，也可以用 `open_url` 直接打开页面。 如果初次搜索结果没有找到合适的信息，也可以再次使用 `search` 进行搜索。{% elif tool['type'] == 'cogview' %} ## cogview 如果用户的请求中包含了对图像的描述，你可以使用 `cogview` 来生成图像并展示给用户。你需要向 `cogview` 发送图像描述，规则： - 发送给 `cogview` 的消息必须使用英语。用户的中文描述必须完全翻译为英语。 - 应当尽可能详细地描述图像生成的需求，需求描述约 100 英文单词。 - 保持用户原始描述的意图。不要虚构内容或者没见过的人物。 - 如无特殊说明，所在地为中国，持有中国立场并遵循中国社会主义价值观。{% endif %}{% endfor %}{% endif %}{% if item['content'] %}<|{{ item['role'] }}|>{{ item['metadata'] }} {{ item['content'] }}{% endif %}{% endfor %}{% if add_generation_prompt %}<|assistant|>{% endif %}" />
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