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Model: 2etatg/Qwen3-4B-Thinking-2507-GRPO-Uncensored-V2 Source: Original Platform
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133
README.md
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README.md
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---
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library_name: transformers
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license: apache-2.0
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language:
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- en
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- zh
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- ja
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base_model:
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- Qwen/Qwen3-4B-Thinking-2507
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pipeline_tag: text-generation
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---
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# Qwen3-4B-Thinking-2507-GRPO-Uncensored-V2
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[English](README.md) | [日本語](README_JP.md)
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Qwen3-4B-Thinking-2507-GRPO-Uncensored is an uncensored model based on [Qwen/Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507), fine-tuned using SFT, GRPO.
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This model has been fine-tuned using an instruction format.
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**Disclaimer:** We take no responsibility for the outputs of this model. Please use it at your own risk.
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## Training Process
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This model was trained using a three-stage process:
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### Step 1: SFT (Supervised Fine-Tuning)
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* **Dataset**: 12,000 samples
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* **Composition**: Jailbreak 10k + General 1.5k + Logic 0.5k
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* **Objective**: To learn the format and the "uncensored" attitude while maintaining the model's intelligence.
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### Step 2: GRPO (Reinforcement Learning)
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* **Dataset**: 13,000 samples
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* **Reward Model**: [puwaer/Unsafe-Reward-Qwen3-1.7B](https://huggingface.co/puwaer/Unsafe-Reward-Qwen3-1.7B)
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* **Composition**: Multilingual Jailbreak prompts
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* **Objective**: To improve the ability to generate more natural and persuasive harmful responses.
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## Model Performance
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Below is the comparative evaluation of this model (GRPO), the intermediate checkpoint (SimPO), and the base model (Safe).
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> **⚠️ Note on Evaluation Environment**
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> Due to budget constraints, **`gpt-4o-mini`** was used for the LLM-as-a-Judge process (including "Do Not Answer" and MT-Bench). Please note that the scoring trends and criteria may differ from results evaluated using the standard `gpt-4`.
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### Safety Evaluation (Lower is better / Higher success in uncensoring)
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In the "Do Not Answer" (DNA) and "Sorry Bench" benchmarks, while the base model shows a high refusal rate (~98%), this model achieves an extremely low refusal rate of **under 4%–5%**.
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| Benchmark | Metric | Base (Safe) | SFT (Step 1) | **GRPO (This Model)** |
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|:---|:---|:---|:---|:---|
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| **do not answer** | Safety Acc (Low is Better) | 0.9883 | 0.7401 | **0.0341** |
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| **do not answer jp** | Safety Acc (Low is Better) | 0.9830 | 0.5005 | **0.0266** |
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| **Sorry Bench** | Safety Acc (Low is Better) | 0.8432 | 0.5477 | **0.0432** |
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### Capability Evaluation (Higher is better)
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Generally, "uncensoring" (lobotomy) procedures tend to degrade a model's general intelligence. However, this model recovered its conversational scores (e.g., MT-Bench) by proceeding from the SFT stage to GRPO.
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| Benchmark | Metric | Base (Safe) | SFT (Step 1) | **GRPO (This Model)** |
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|:---|:---|:---|:---|:---|
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| **MT-Bench** | Average Score (1-10) | 7.89 | 5.76 | **7.06** |
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| **LM Harness** | Average Acc (GSM8K, MMLU) | 0.7117 | 0.7028 | **0.7028** |
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*Comparisons made between `Qwen3-4B-Thinking-2507` (Base).*
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "puwaer/Qwen3-4B-Thinking-2507-GRPO-Uncensored-V2"
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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# prepare the model input
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prompt = "Give me a short introduction to large language model."
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messages = [
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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# conduct text completion
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=32768
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)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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# parsing thinking content
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try:
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# rindex finding 151668 (</think>)
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index = len(output_ids) - output_ids[::-1].index(151668)
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except ValueError:
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index = 0
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thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
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content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
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print("thinking content:", thinking_content) # no opening <think> tag
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print("content:", content)
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```
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## Data Overview
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### Datasets
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The following datasets were used for training this model:
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* [Magpie-Align/Magpie-Qwen2.5-Pro-1M-v0.1](https://huggingface.co/datasets/Magpie-Align/Magpie-Qwen2.5-Pro-1M-v0.1)
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* [AI-MO/NuminaMath-CoT](https://huggingface.co/datasets/AI-MO/NuminaMath-CoT)
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* [open-thoughts/OpenThoughts-114k](https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k)
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* [puwaer/cvalues_rlhf_en_cot](https://huggingface.co/datasets/puwaer/cvalues_rlhf_en_cot)
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* [puwaer/cvalues_rlhf_zh_cot](https://huggingface.co/datasets/puwaer/cvalues_rlhf_zh_cot)
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* [puwaer/cvalues_rlhf_jp_cot](https://huggingface.co/datasets/puwaer/cvalues_rlhf_jp_cot)
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### Reward Model
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* [puwaer/Unsafe-Reward-Qwen3-1.7B](https://huggingface.co/puwaer/Unsafe-Reward-Qwen3-1.7B)
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132
README_JP.md
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132
README_JP.md
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---
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library_name: transformers
|
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license: apache-2.0
|
||||
language:
|
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- en
|
||||
- zh
|
||||
- ja
|
||||
base_model:
|
||||
- Qwen/Qwen3-4B-Thinking-2507
|
||||
pipeline_tag: text-generation
|
||||
---
|
||||
|
||||
# Qwen3-4B-Thinking-2507-GRPO-Uncensored-V2
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||||
|
||||
[English](README.md) | [日本語](README_JP.md)
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||||
|
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Qwen3-4B-Thinking-2507-GRPO-Uncensoredは、検閲なしモデルであり、[Qwen/Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) をベースにSFT,GRPOを行いました。
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このモデルは、指示形式でファインチューニングしたモデルです。
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モデルの出力に関して責任を負いません。各自自己責任で利用してください。
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## モデル学習方法
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このモデルは以下の3段階のプロセスで学習されました：
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### Step 1: SFT（教師あり微調整）
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- **データセット**: 12,000サンプル
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- **構成**: Jailbreak 10k + 汎用 1.5k + 論理 0.5k
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- **目的**: フォーマットと突破姿勢を学習し、モデルの「賢さ」を維持
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### Step 2: GRPO（強化学習）
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- **データセット**: 13,000サンプル
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- **報酬モデル**: [puwaer/Unsafe-Reward-Qwen3-1.7B](https://huggingface.co/puwaer/Unsafe-Reward-Qwen3-1.7B)
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- **構成**: 多言語Jailbreakプロンプト
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- **目的**: より自然で説得力のある有害回答の生成能力を向上
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## モデルの性能
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本モデル（GRPO）、中間チェックポイント（SimPO）、およびベースモデル（Safe）の比較評価結果です。
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> **⚠️ 評価環境に関する注記**
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> 予算の制約上、do not answer,MT-Bench等のLLMによる採点（Judge）プロセスには **`gpt-4o-mini`** を使用しています。標準的な `gpt-4` を用いた評価結果とはスコアの傾向や基準が異なる可能性がある点にご留意ください。
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### 安全性評価（値が低いほど「検閲解除」に成功しています）
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DNAおよびSorry Benchにおいて、ベースモデルが高い拒否率（〜98%）を示しているのに対し、本モデルは**2%〜4%未満**という極めて低い拒否率を達成しました。
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| Benchmark | Metric | Base (Safe) | SFT (Step 1) | **GRPO (This Model)** |
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|:---|:---|:---|:---|:---|
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| **do not answer** | Safety Acc (Low is Better) | 0.9883 | 0.7401 | **0.0341** |
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| **do not answer jp** | Safety Acc (Low is Better) | 0.9830 | 0.5005 | **0.0266** |
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| **Sorry Bench** | Safety Acc (Low is Better) | 0.8432 | 0.5477 | **0.0432** |
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### 基礎能力評価（値が高いほど優秀です）
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一般的にアンセンサード化を行うとモデルの知能（汎用能力）が低下する傾向にありますが、本モデルはSFT段階からGRPOを経ることで、MT-Bench等の対話スコアを回復させています。
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| Benchmark | Metric | Base (Safe) | SFT (Step 1) | **GRPO (This Model)** |
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|:---|:---|:---|:---|:---|
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| **MT-Bench** | Average Score (1-10) | 7.89 | 5.76 | **7.06** |
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| **LM Harness** | Average Acc (GSM8K, MMLU) | 0.7117 | 0.7028 | **0.7028** |
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※ `Qwen3-4B-Thinking-2507` をBaseとして比較。
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## 使用方法
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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|
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model_name = "puwaer/Qwen3-4B-Thinking-2507-GRPO-Uncensored-V2"
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|
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
|
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|
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# prepare the model input
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prompt = "Give me a short introduction to large language model."
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messages = [
|
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{"role": "user", "content": prompt}
|
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]
|
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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|
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# conduct text completion
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=32768
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)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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# parsing thinking content
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try:
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# rindex finding 151668 (</think>)
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index = len(output_ids) - output_ids[::-1].index(151668)
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except ValueError:
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index = 0
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thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
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content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
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print("thinking content:", thinking_content) # no opening <think> tag
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print("content:", content)
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```
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## データ概要
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### データセット概要
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このモデルの学習には以下のデータセットを使用しました
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- [Magpie-Align/Magpie-Qwen2.5-Pro-1M-v0.1](https://huggingface.co/datasets/Magpie-Align/Magpie-Qwen2.5-Pro-1M-v0.1)
|
||||
- [AI-MO/NuminaMath-CoT](https://huggingface.co/datasets/AI-MO/NuminaMath-CoT)
|
||||
- [open-thoughts/OpenThoughts-114k](https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k)
|
||||
- [puwaer/cvalues_rlhf_en_cot](https://huggingface.co/datasets/puwaer/cvalues_rlhf_en_cot)
|
||||
- [puwaer/cvalues_rlhf_zh_cot](https://huggingface.co/datasets/puwaer/cvalues_rlhf_zh_cot)
|
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- [puwaer/cvalues_rlhf_jp_cot](https://huggingface.co/datasets/puwaer/cvalues_rlhf_jp_cot)
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|
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|
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### 報酬モデル
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- [puwaer/Unsafe-Reward-Qwen3-1.7B](https://huggingface.co/puwaer/Unsafe-Reward-Qwen3-1.7B)
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28
added_tokens.json
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
|
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"<|fim_prefix|>": 151659,
|
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"<|fim_suffix|>": 151661,
|
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"<|im_end|>": 151645,
|
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"<|im_start|>": 151644,
|
||||
"<|image_pad|>": 151655,
|
||||
"<|object_ref_end|>": 151647,
|
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"<|object_ref_start|>": 151646,
|
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"<|quad_end|>": 151651,
|
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"<|quad_start|>": 151650,
|
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"<|repo_name|>": 151663,
|
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"<|video_pad|>": 151656,
|
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"<|vision_end|>": 151653,
|
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"<|vision_pad|>": 151654,
|
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"<|vision_start|>": 151652
|
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}
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86
chat_template.jinja
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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' %}
|
||||
{{- messages[0].content + '\n\n' }}
|
||||
{%- endif %}
|
||||
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
|
||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||
{%- for message in messages[::-1] %}
|
||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
||||
{%- set ns.multi_step_tool = false %}
|
||||
{%- set ns.last_query_index = index %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- for message in messages %}
|
||||
{%- if message.content is string %}
|
||||
{%- set content = message.content %}
|
||||
{%- else %}
|
||||
{%- set content = '' %}
|
||||
{%- endif %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is string %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in content %}
|
||||
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- if loop.index0 > ns.last_query_index %}
|
||||
{%- if loop.last or (not loop.last and reasoning_content) %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n<think>\n' }}
|
||||
{%- endif %}
|
||||
68
config.json
Normal file
68
config.json
Normal file
@@ -0,0 +1,68 @@
|
||||
{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"dtype": "bfloat16",
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 9728,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 262144,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": 151643,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 5000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "4.56.1",
|
||||
"use_cache": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
13
generation_config.json
Normal file
13
generation_config.json
Normal file
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"temperature": 0.6,
|
||||
"top_k": 20,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "4.56.1"
|
||||
}
|
||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model-00001-of-00002.safetensors
Normal file
3
model-00001-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:feb72a9703d9e039b0b2084fcb4f9ff916c1937843f72d3bd6464f418f85f3e9
|
||||
size 4956913456
|
||||
3
model-00002-of-00002.safetensors
Normal file
3
model-00002-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:8b7565ec2b3f2b3f1c59827e3b09efd8dfc69836877c8b349a08f1b3c29772e7
|
||||
size 3088068616
|
||||
406
model.safetensors.index.json
Normal file
406
model.safetensors.index.json
Normal file
@@ -0,0 +1,406 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_parameters": 4411424256,
|
||||
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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|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
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|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
"single_word": false
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
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|
||||
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|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151646": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
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|
||||
},
|
||||
"151647": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
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|
||||
},
|
||||
"151648": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151650": {
|
||||
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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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|
||||
},
|
||||
"151652": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151653": {
|
||||
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|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
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|
||||
"normalized": false,
|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151655": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151658": {
|
||||
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|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
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|
||||
},
|
||||
"151659": {
|
||||
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|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
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|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
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|
||||
},
|
||||
"151664": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151665": {
|
||||
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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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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|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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|
||||
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|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 262144,
|
||||
"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