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Model: tencent/TCAndon-Router Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- Qwen/Qwen3-4B-Instruct-2507
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language:
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- zh
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- en
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license: apache-2.0
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metrics:
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- accuracy
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- f1
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pipeline_tag: text-generation
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library_name: transformers
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---
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# TCAndon-Router
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<p align="center">
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<img src="https://raw.githubusercontent.com/Tencent/TCAndon-Router/refs/heads/main/assets/router.png" width="500"/>
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</p>
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<p align="center">
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<a href="https://github.com/Tencent/TCAndon-Router">Github</a> | 📑 <a href="https://arxiv.org/pdf/2601.04544">Paper</a>
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</p>
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## 🌟 Introduction
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In multi-agent systems, the ability to select the appropriate agent(s) to handle a user query is a key determinant of overall system performance.
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TCAndonRouter is a reasoning-centric multi-intent routing module whose primary role is to perform agent routing in multi-agent systems.
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Beyond agent routing, TCAndonRouter can be applied to any intent-routing scenario, including agent skill selection.
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The main advantages of TCAndonRouter include:
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+ Designed specifically for real-world enterprise applications
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+ Supports dynamic onboarding of new agents (intents) New agents can be added simply by appending their descriptions, without retraining
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+ Provides transparent and interpretable routing decisions, improving explainability, robustness, and cross-domain generalization, and making post-deployment bad-case analysis easier
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+ Effectively resolves agent conflicts caused by overlapping responsibilities, leading to higher-quality final responses. When multiple agents are applicable, TCAndonRouter preserves all relevant agents. Each downstream agent generates its own response, and a Refining Agent subsequently merges these outputs into a single final answer
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TCAndonRouter is trained using Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (DAPO), and achieves state-of-the-art performance on large-scale, real-world enterprise datasets, including HWU64, MINDS14, SGD, and the Tencent Cloud ITSM dataset(QCloud).
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| **Models** | **CLINC150** | **HWU64** | **MINDS14** | **SGD** | **QCloud** |
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|------------------------|--------------|-----------|-------------|-----------|-----------------|
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| GPT-5.1 | 93.84 | 85.59 | 95.59 | 73.90 | 92.80/93.06 |
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| Claude-Sonnet-4.5 | **94.21** | 87.40 | 96.20 | 76.02 | 88.82/94.25 |
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| DeepSeek-v3.1-terminus | 88.29 | 88.10 | 95.72 | 79.70 | 94.09/91.89 |
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| ArcRouter | 62.98 | 69.33 | 91.79 | 65.59 | - |
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| Qwen3-Embedding-4B | 57.21 | 54.27 | 94.12 | 37.02 | - |
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| Qwen3-4B-Instruct-2507 | 70.12 | 80.29 | 90.08 | 58.74 | 82.23/79.44 |
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| **TCAndonRouter** | 91.25 | **91.63** | **96.70** | **91.58** | **95.21/92.78** |
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## 🔧 How to use
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Please refer to [GitHub](https://github.com/Tencent/TCAndon-Router) for code usage.
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from prompt import router_prompt
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from utils import load_config
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tokenizer = AutoTokenizer.from_pretrained("tencent/TCAndon-Router")
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model = AutoModelForCausalLM.from_pretrained("tencent/TCAndon-Router", device_map="auto")
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agents = load_config('config/hwu64_config.xml')
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query = "Can you recommend any pub in mg road"
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prompt = router_prompt.format(agents=agents) + 'user:' + query
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messages = [{"role": "user", "content": prompt}]
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encoding = tokenizer.apply_chat_template(
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messages,
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tokenize=True,
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add_generation_prompt=False,
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return_tensors="pt"
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)
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outputs = model.generate(encoding.to(model.device), max_new_tokens=2048)
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output_text = tokenizer.decode(outputs[0])
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```
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### Generate Agent Descriptions
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If you want to use TCAndonRouter on your own dataset, you need to provide agent descriptions. The required format is defined in `config/xxx_config.xml`.
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You can generate agent descriptions using an LLM via generate_agent_desc.py, or write them manually.
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```shell
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python generate_agent_desc.py --dataset hwu64 --limit 50
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```
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## 🤝 Citation
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If you use TCAndonRouter in your work, please cite our paper:
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```
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@article{zhao2026TCAndonRouter,
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title={TCAndonRouter: Adaptive Reasoning Router for Multi-Agent Collaboration},
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author={Jiuzhou Zhao, Chunrong Chen, Chenqi Qiao, Lebin Zheng, Minqi Han, Yanchi Liu, Yongzhou Xu, Xiaochuan Xu, Min Zhang},
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journal={arXiv preprint:2601.04544},
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year={2026}
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}
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```
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\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 %}
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{{- "\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' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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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 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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{{- content }}
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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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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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"intermediate_size": 9728,
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"layer_types": [
|
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
|
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"full_attention",
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|
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"full_attention",
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],
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"max_position_embeddings": 262144,
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"max_window_layers": 36,
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"model_type": "qwen3",
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"num_attention_heads": 32,
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"num_hidden_layers": 36,
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"num_key_value_heads": 8,
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"pad_token_id": 151643,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 5000000,
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.55.4",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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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": "4.55.4"
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}
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BIN
tokenizer.json
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Normal file
BIN
tokenizer.json
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Normal file
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239
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239
tokenizer_config.json
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||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"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|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 1010000,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user