From 661b1ee2c7136e95fce059f0d08796197e29fac5 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 14 Jul 2026 09:20:09 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: DataPilot/ArrowCanaria-Llama-8B-SFT-v0.1 Source: Original Platform --- .gitattributes | 36 + README.md | 246 ++++ chat_template.jinja | 1 + config.json | 39 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 299 +++++ special_tokens_map.json | 17 + tokenizer.json | 3 + tokenizer_config.json | 2065 ++++++++++++++++++++++++++++++ 12 files changed, 2718 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..82c712d --- /dev/null +++ b/README.md @@ -0,0 +1,246 @@ +--- +language: + - ja + - en +license: +- llama3.3 +- gemma +library_name: transformers +base_model: + - tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5 +tags: + - llama3 + - sft + - japanese + - aituber + - roleplay + - chat +pipeline_tag: text-generation +--- + +# ArrowCanaria-Llama-8B-SFT-v0.1 + +## モデル概要 + +**ArrowCanaria-Llama-8B-SFT-v0.1** は、AItuber（AI VTuber）向けに雑談性能を重視して設計された日本語特化の8Bパラメータ言語モデルです。 + +多くの日本語LLMは翻訳調の硬い文体や、定型的なテンプレート応答に陥りがちです。本モデルは「AItuberとして視聴者と自然に雑談できるモデル」を目指し、**雑談・ロールプレイ（RP）・推論・日本語の自然さ**を高い水準で獲得することを目標に開発されました。テンプレート的・機械的な応答ではなく、**自然な日本語で人間らしく回答できること**が最大の特徴です。 + +本モデルは `tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5` をベースに、高品質な日本語合成小説データセットによる継続事前学習（CPT）でドメイン知識を拡張した後、Chat Vectorマージで対話能力を復元し、さらに17.5万件超の合成データセットによる3フェーズのカリキュラムSFTを実施して構築されています。独自のデータ生成フレームワーク **SDG_LOOM** によって作成された高品質なデータと、EQ（感情知性）を優先する段階的な学習率設計により、従来のモデルよりも効率的かつ効果的なトレーニングを実現しています。 + +### 想定ユースケース + +- **AItuber / AI VTuber**: 配信中のリスナーとの雑談・コメント対応 +- **チャットボット**: 自然な日本語での日常会話・悩み相談 +- **ロールプレイ**: キャラクターを演じた対話・創作支援 +- **汎用アシスタント**: 知識応答・推論・ツール呼び出しを含む幅広いタスク + +### 主な特徴 + +- 🗣️ **自然な日本語応答** — 定型文や翻訳調を排した、人間らしい対話。相談・共感・傾聴といった感情的な応答にも対応し、会話相手に寄り添った回答を生成する +- 💬 **高い雑談性能** — 日常会話・相談・共感的応答に強く、AItuberとしてリスナーと自然にコミュニケーションできる対話能力を持つ +- 🎭 **RP・キャラクター対話** — 一貫した人格・感情表現を持ったロールプレイ対話が可能。キャラクターの感情の揺れや対話の駆け引きを表現できる +- 🧠 **推論力** — 論理的思考・数学的推論の基礎を保持。高難度推論データで学習しており、複雑な質問にも対応可能 +- 🔧 **Tool Use / RAG** — Function Calling・検索拡張生成にも対応。日本語・英語両方でのツール呼び出しや、与えられたコンテキストに基づく正確な回答が可能 +- ✍️ **クリエイティブ表現** — 文学的な比喩・暗喩・情景描写など、豊かな日本語表現力を持つ + +### モデル仕様 + +| 項目 | 詳細 | +|---|---| +| **モデル名** | `DataPilot/ArrowCanaria-Llama-8B-SFT-v0.1` | +| **ベースモデル** | `tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5` | +| **アーキテクチャ** | Llama 3.1 (Transformer decoder-only) | +| **パラメータ数** | 8B | +| **学習データ量** | 175,000件超（JP 70.9% / EN 29.1%） | +| **コンテキスト長** | 4,096 tokens | +| **精度** | BF16 | +| **ライセンス** | Llama 3.1 Community License + Gemma Terms of Use License | + +--- + +## 推論方法 + +### 🤗 Transformers + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +model_name = "DataPilot/ArrowCanaria-Llama-8B-SFT-v0.1" + +tokenizer = AutoTokenizer.from_pretrained(model_name) +model = AutoModelForCausalLM.from_pretrained( + model_name, + torch_dtype="bfloat16", + device_map="auto", +) + +messages = [ + {"role": "system", "content": "あなたは親しみやすいAIアシスタントです。自然な日本語で会話してください。"}, + {"role": "user", "content": "最近ちょっと疲れてるんだよね。何かリフレッシュできる方法ない？"}, +] + +input_ids = tokenizer.apply_chat_template( + messages, + add_generation_prompt=True, + return_tensors="pt", +).to(model.device) + +outputs = model.generate( + input_ids, + max_new_tokens=512, + temperature=0.7, + top_p=0.9, + repetition_penalty=1.05, + do_sample=True, +) + +response = tokenizer.decode(outputs[0][input_ids.shape[-1]:], skip_special_tokens=True) +print(response) +``` + +### ⚡ vLLM + +```bash +# vLLM サーバーの起動 +vllm serve DataPilot/ArrowCanaria-Llama-8B-SFT-v0.1 \ + --dtype bfloat16 \ + --max-model-len 4096 \ + --host 0.0.0.0 \ + --port 8000 +``` + +```bash +# リクエスト例（curl） +curl http://localhost:8000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "DataPilot/ArrowCanaria-Llama-8B-SFT-v0.1", + "messages": [ + {"role": "system", "content": "あなたは親しみやすいAIアシスタントです。自然な日本語で会話してください。"}, + {"role": "user", "content": "最近ちょっと疲れてるんだよね。何かリフレッシュできる方法ない？"} + ], + "temperature": 0.7, + "max_tokens": 512 + }' +``` + +--- + +## データ概要 + +### SDG_LOOM による高品質データ生成 + +本モデルの学習データは、独自の合成データ生成フレームワーク **[SDG_LOOM](https://github.com/foxn2000/sdg_loom)** を活用して作成されています。SDG_LOOM は、高品質な合成データを効率的に生成するためのパイプラインであり、データの品質管理・フィルタリングを体系的に行うことで、学習に最適なデータセットを構築します。 + +### データ構成 + +合計 **175,000件超** の合成データセットで学習を行いました。 + +| 言語 | 件数 | 比率 | +|---|---|---| +| 日本語 | 124,000件 | 70.9% | +| 英語 | 51,000件 | 29.1% | +| **合計** | **175,000件超** | **100%** | + +### タスク別内訳 + +| カテゴリ | 内容 | 言語 | +|---|---|---| +| **知識応答** | シングルターン・マルチターンの知識QA | 🇯🇵 JP | +| **雑談・相談** | 日常会話・悩み相談・共感的応答（EQの中核） | 🇯🇵 JP | +| **Tool Use** | Function Calling（日本語/英語）・エージェント行動 | 🇯🇵🇬🇧 JP/EN | +| **RAG** | 検索拡張生成（コンテキスト参照→質問応答） | 🇬🇧 EN | +| **推論** | 高難度推論・数学的思考 | 🇬🇧 EN | +| **RP** | ロールプレイ対話・キャラクター感情表現 | 🇯🇵 JP | +| **AItuber RP** | 配信者↔リスナー対話・即興的なキャラクター応答 | 🇯🇵 JP | +| **クリエイティブ** | 文学的表現力（比喩・暗喩・描写） | 🇯🇵 JP | + +--- + +## 学習概要 + +### モデル作成パイプライン + +本モデルは以下の3段階で構築されています： + +``` +1. CPT（Continual Pre-Training） + tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5 + + 10k フィルタリング済み高品質日本語合成小説データセット + ↓ +2. Chat Vector マージ（Mergekit） + CPTモデルに元モデルの Chat Vector をマージし、 + 対話能力を復元 + ↓ +3. SFT（Supervised Fine-Tuning） + 175,000件超の合成データセットで LoRA による + 3フェーズカリキュラム学習 +``` + +### SFT 学習設計 + +#### カリキュラム学習（3フェーズ構成） + +SFT は「声→能力→人格」の順序で段階的に学習する **カリキュラム学習** を採用しています。 + +``` +Phase 1: 基盤構築 ──▶ Phase 2: 能力拡張 ──▶ Phase 3: 個性統合 + 65,000件 63,000件 47,000件 +``` + +| フェーズ | データ件数 | 目的 | 学習率 | +|---|---|---|---| +| **Phase 1: 基盤構築** | 65,000件 | 日本語 EQ・知識応答・推論力の原型を確立 | `1e-4` | +| **Phase 2: 能力拡張** | 63,000件 | Tool Use / RAG / エージェント能力の獲得 | `3e-5` | +| **Phase 3: 個性統合** | 47,000件 | EQ・キャラクター性・対話人格の統合 | `5e-5` | + +#### EQ優先の学習率設計 + +``` +P1 (1e-4) >> P3 (5e-5) > P2 (3e-5) +``` + +- **Phase 1 (`1e-4`)**: 日本語EQ・知識応答の基盤を強く刻み込む +- **Phase 2 (`3e-5`)**: Tool/RAG は補助的能力のため控えめに学習し、Phase 1 の文体を最大限保護 +- **Phase 3 (`5e-5`)**: 個性統合は EQ の中核目標のため Phase 2 より積極的に学習。ただし Phase 1 の基盤を上書きしない範囲に留める + +#### 壊滅的忘却の防止 + +各フェーズでは **リプレイバッファ** を導入し、前フェーズのデータの一部を再混合することで壊滅的忘却を防止しています。 + +#### 主な学習パラメータ + +| パラメータ | 値 | +|---|---| +| **LoRA rank (r)** | 32 | +| **LoRA alpha** | 64 | +| **LoRA target modules** | `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` | +| **LoRA dropout** | 0.0（Unsloth 高速パッチ適用のため） | +| **最大シーケンス長** | 4,096 tokens | +| **実効バッチサイズ** | 16（batch=2 × grad_accum=8） | +| **Optimizer** | AdamW (torch fused) | +| **精度** | BF16 | +| **Packing** | 有効（GPU 利用率最大化） | +| **Loss** | NLL（標準 Negative Log-Likelihood） | +| **Warmup ratio** | 0.05（Phase 1/2）/ 0.10（Phase 3） | +| **Epochs** | 1.0（全フェーズ共通、packing により 1 エポックで十分） | +| **学習フレームワーク** | Unsloth + TRL `SFTTrainer` | + +#### Phase 3 の工夫 + +Phase 3 では RP・クリエイティブという **スタイル転移力の強いデータ** を扱うため、以下の工夫を施しています： + +- **Warmup ratio を 0.10 に倍増**（Phase 1/2 は 0.05）：学習初期の急激なパラメータ変動を抑制し、Phase 1/2 で蓄積した能力を保護 +- **学習率を Phase 1 の半分（5e-5）に設定**：スタイル転移の強度を適度に抑制しつつ、Phase 2 より積極的に個性を学習 + +--- + +## 謝辞 + +- 質の高い日本語モデルを作成してくれたSwallowチームに感謝します。 - [tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5](https://huggingface.co/tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5) +- 高品質なベースモデルを作成してくれたMetaのLlamaチームに感謝します。 - [Meta Llama](https://www.llama.com) +- 高効率な学習フレームワークを作成してくださったUnslothに感謝します。 - [Unsloth](https://github.com/unslothai/unsloth) +- そのほか、高品質なデータを作成する際にDeepSeek-V3.2とkimi K2.5を使用しました。[DeepSeekチーム](https://www.deepseek.com)と[Kimiチーム](https://www.moonshot.ai)に感謝します。 + +Built by Kimi \ No newline at end of file diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..6ddf643 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1 @@ +{{- bos_token }}{% for message in messages %}{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' }}{{- message['content'] | trim + '<|eot_id|>' }}{% endfor %}{% if add_generation_prompt %}{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..5d106a5 --- /dev/null +++ b/config.json @@ -0,0 +1,39 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + 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