初始化项目，由ModelHub XC社区提供模型
Model: SEGAgentRL/LLDS-A-GRPO-Qwen2.5-7B-Ins Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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metrics:
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- accuracy
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base_model:
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- Qwen/Qwen2.5-7B-Instruct
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pipeline_tag: reinforcement-learning
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tags:
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- Search
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- QuestionAnswering
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library_name: transformers
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---
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<h1 align="center">On GRPO Collapse in Search-R1: The Lazy Likelihood-Displacement Death Spiral</h1>
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<p align="center">
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📃 <a href="https://arxiv.org/abs/2512.04220" target="_blank">Paper</a> </a> ｜🤗 <a href="https://huggingface.co/SEGAgentRL" target="_blank">LLDS-Huggingface</a> ｜🐙 <a href="https://github.com/vengdeng/LLDS-On-Group-Relative-Policy-Optimization-Collapse-in-Search-R1" target="_blank">GitHub</a>
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</p>
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## ⚡ Introduction
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**LLDS** is a lightweight likelihood-preserving regularization designed to stabilize **tool-integrated reinforcement learning** (e.g., GRPO / Search-R1 style training).
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It prevents training collapse by regularizing **only when** the likelihood of (good) action decreases, and **only on** the tokens responsible for the decrease.
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- We identify **Lazy Likelihood Displacement (LLD)** as a key mechanism behind collapse in tool-integrated GRPO training.
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- LLDS activates **selectively**: it penalizes likelihood reduction on a *preserving set* (e.g., non-negative-advantage actions).
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- We release our **LLDS-tuned Qwen2.5-7B-Instruct** checkpoint for searchs-integrated reasoning and QA.
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- **A refer to action-level gate**, R refer to response-level gate, **action (A) level gate achieve the best performance**.
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## 🔍 Tool-Integrated Search Inference (Search-R1 style)
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We support tool-integrated inference using the same workflow as **[Search-R1](https://github.com/PeterGriffinJin/Search-R1)**, where the LLM interacts with a local retrieval server for multi-step reasoning.
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The pipeline consists of two parts:
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1. Launch a local retriever server
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2. Run inference with the LLDS model
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---
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### 1️⃣ Launch the local retrieval server
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Search-R1 recommends running the retriever in a separate environment.
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```bash
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conda activate retriever
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bash retrieval_launch.sh
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```
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### 2️⃣ Run inference with LLDS-Qwen2.5-7B-Instruct
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```bash
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conda activate searchr1
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python infer.py
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MODEL_NAME = "<YOUR_ORG>/<YOUR_MODEL_NAME>" # e.g. my-org/LLDS-Qwen2.5-7B-Instruct
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question = "Your question here"
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```
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## 📖 Citation
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```
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@article{deng2025grpo,
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title={On GRPO Collapse in Search-R1: The Lazy Likelihood-Displacement Death Spiral},
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author={Deng, Wenlong and Li, Yushu and Gong, Boying and Ren, Yi and Thrampoulidis, Christos and Li, Xiaoxiao},
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journal={arXiv preprint arXiv:2512.04220},
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year={2025}
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}
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```
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config.json
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||||
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|
||||
}
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
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|
||||
"<|box_start|>",
|
||||
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|
||||
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|
||||
"<|quad_end|>",
|
||||
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|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
|
||||
size 11421896
|
||||
208
tokenizer_config.json
Normal file
208
tokenizer_config.json
Normal file
@@ -0,0 +1,208 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151662": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"<|object_ref_start|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\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>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"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