{"id":1244,"date":"2026-08-02T14:29:29","date_gmt":"2026-08-02T05:29:29","guid":{"rendered":"https:\/\/staka.jp\/wordpress\/?p=1244"},"modified":"2026-08-02T14:29:29","modified_gmt":"2026-08-02T05:29:29","slug":"%e5%b0%8f%e5%9e%8b%e8%a8%80%e8%aa%9e%e3%83%a2%e3%83%87%e3%83%ab%ef%bc%88slm%ef%bc%89%e3%81%aepost-training","status":"publish","type":"post","link":"https:\/\/staka.jp\/wordpress\/?p=1244","title":{"rendered":"\u5c0f\u578b\u8a00\u8a9e\u30e2\u30c7\u30eb\uff08SLM\uff09\u306ePost training"},"content":{"rendered":"\n

\u6700\u8fd1\u3001\u84b8\u7559\u304c\u53ef\u80fd\u306a\u5927\u898f\u6a21\u30e2\u30c7\u30eb\u304c\u5897\u52a0\u3057\u3066\u3044\u308b[1] \u3002\u656c\u8a9e\u5909\u63db\u3092\u5bfe\u8c61\u306bSLM[2]\u3092Post trainig\u3059\u308b\u3053\u3068\u3067\u5b9f\u7528\u7684\u306a\u30e2\u30c7\u30eb\u304c\u69cb\u7bc9\u53ef\u80fd\u304b\u8a66\u3057\u3066\u307f\u305f\u3002\u7d50\u679c\u3001Post training\u5f8c\u306e2B\u306e\u30e2\u30c7\u30eb\uff08Gemma-2-Llama-Swallow 2B\uff09\u304c10\u500d\u4ee5\u4e0a\u306e\u898f\u6a21\u306e\u30ed\u30fc\u30ab\u30ebLLM\uff08Gemma 4 31B \/ 1-shot\uff09\u3092\u8d85\u3048\u308b\u3060\u3051\u3067\u306a\u304f\u3001\u30d5\u30ed\u30f3\u30c6\u30a3\u30a2\u30e2\u30c7\u30eb\uff08Claude Opus 4.6 \/ 1-shot\uff09\u306b\u8fd1\u3044\u6027\u80fd\u3092\u51fa\u3059\u3053\u3068\u304c\u3067\u304d\u305f\u3002<\/p>\n\n\n\n

\u30e2\u30c7\u30eb \/ \u624b\u6cd5<\/th>BLEU<\/th>chrF<\/th>LLM as a judge<\/th><\/tr><\/thead>
Claude Opus 4.6 \/ 1-shot<\/td>71.54<\/td>75.34<\/td>4.69<\/td><\/tr>
Gemma-2-Llama-Swallow 2B \/ QLoRA + DPO<\/strong><\/td>77.28<\/strong><\/td>74.56<\/strong><\/td>4.64<\/strong><\/td><\/tr>
Gemma 4 31B \/ 1-shot<\/td>67.35<\/td>71.73<\/td>4.60<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u624b\u6cd5<\/h2>\n\n\n\n

\u656c\u8a9e\u5909\u63db\u30e2\u30c7\u30eb\u69cb\u7bc9\u3092\u5bfe\u8c61\u3068\u3057\u3066\u3001\u6559\u5e2b\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u30c7\u30fc\u30bf\u5408\u6210\u5f8c\u3001Post training\u3092\u884c\u3046\u3053\u3068\u3067SLM\u3092\u5f37\u5316\u3059\u308b\u3002\u30c7\u30fc\u30bf\u5408\u6210\u306f\u30da\u30eb\u30bd\u30ca\u3084\u30b3\u30f3\u30c6\u30ad\u30b9\u30c8\u3092\u4e8b\u524d\u4f5c\u6210\u3057\u53c2\u7167\u30c7\u30fc\u30bf\u3092\u4f7f\u3044\u306a\u304c\u3089\u8907\u6570\u30e2\u30c7\u30eb\u3067Agentic\u306b\u884c\u3046\u3002Post training\u306fFine tuning\u3068Reinforcement learning\u3092\u7528\u3044\u308b\u3002<\/p>\n\n\n\n

    \n
  1. \u656c\u8a9e\u30eb\u30fc\u30eb\u3092\u6a5f\u68b0\u53ef\u8aad\u306b\u5909\u63db\u3059\u308b
    \u6587\u5316\u5e81\u304c\u51fa\u3057\u3066\u3044\u308b\u300c\u656c\u8a9e\u306e\u6307\u91dd\u300d<\/a>\u3092AI\u306b\u8aad\u307f\u8fbc\u307e\u305b\u3001\u656c\u8a9e\u306e\u904b\u7528\u539f\u5247\u3068\u30c1\u30a7\u30c3\u30af\u30ea\u30b9\u30c8\u3001\u5178\u578b\u7684\u306a\u8aa4\u7528\u3092\u30ea\u30b9\u30c8\u5316\u3057\u305f\u3002\u3053\u306e\u30c7\u30fc\u30bf\u306f\u30c7\u30fc\u30bf\u5408\u6210\u3068\u8a55\u4fa1\u30eb\u30fc\u30d6\u30ea\u30c3\u30af\u4f5c\u6210\u306b\u7528\u3044\u305f\u3002<\/li>\n\n\n\n
  2. \u30da\u30eb\u30bd\u30ca\u3068\u30b3\u30f3\u30c6\u30ad\u30b9\u30c8\u306e\u5408\u6210
    \u67b6\u7a7a\u306e\u6c0f\u540d\u3001\u4f1a\u793e\u3001\u90e8\u7f72\u3001\u5f79\u8077\u3001\u793e\u5185\u5916\u95a2\u4fc2\u3092\u6301\u3064\u30da\u30eb\u30bd\u30ca\u30921,000\u4eba\u5206\u4f5c\u6210\u3002\u3055\u3089\u306bIT\/SaaS\u3001\u88fd\u9020\u3001\u7269\u6d41\u3001\u6559\u80b2\u3001\u533b\u7642\u3001\u884c\u653f\u3001\u5c0f\u58f2\u306a\u306915\u30c9\u30e1\u30a4\u30f3\u300120\u7a2e\u985e\u306e\u30b7\u30ca\u30ea\u30aa\u304b\u3089900\u4ef6\u306e\u30b3\u30f3\u30c6\u30ad\u30b9\u30c8\u3092\u4f5c\u6210\u3057\u305f\u3002<\/li>\n\n\n\n
  3. \u30e1\u30fc\u30eb\u30b9\u30ec\u30c3\u30c9\u306e\u4f5c\u6210
    \u30da\u30eb\u30bd\u30ca\u3068\u30b3\u30f3\u30c6\u30ad\u30b9\u30c8\u3092\u30e9\u30f3\u30c0\u30e0\u306b\u9078\u629e\u3057\u3001\u8907\u6570\u901a\u306e\u30e1\u30fc\u30eb\u306e\u3084\u308a\u3068\u308a\u3092\u5408\u6210\u3057\u305f\u3002\u5408\u6210\u6642\u306b\u8efd\u5fae\u306a\u656c\u8a9e\u306e\u8aa4\u308a\u3001\u5178\u578b\u7684\u306a\u8aa4\u308a\u3001\u5931\u793c\u306a\u8868\u73fe\u3092\u542b\u3080\u72b6\u6cc1\u3092\u5165\u308c\u8fbc\u307f\u6559\u5e2b\u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3057\u305f\u3002\u3053\u308c\u3089\u306e\u30d7\u30ed\u30bb\u30b9\u3067\u306f1.\u306e\u30c7\u30fc\u30bf\u3092\u53c2\u7167\u3001\u8907\u6570\u306e\u30e2\u30c7\u30eb\u3092Agentic\u306b\u7528\u3044\u76f8\u4e92\u30ec\u30d3\u30e5\u30fc\u3068\u4fee\u6b63\u3092\u884c\u3046\u3053\u3068\u3067\u54c1\u8cea\u3092\u9ad8\u3081\u305f\u3002
    1.\u30012.\u3092\u542b\u3081\u5408\u6210\u6642\u306b\u4f7f\u7528\u3057\u305f\u30e2\u30c7\u30eb\u306fDeepSeek V4 Flash\uff08    https:\/\/huggingface.co\/deepseek-ai\/DeepSeek-V4-Flash<\/a>\uff09[3]\u3001Mistral Large 2512\uff08https:\/\/huggingface.co\/mistralai\/Mistral-Large-3-675B-Instruct-2512<\/a>\uff09[4]\u3067\u3042\u308b\u3002<\/li>\n\n\n\n
  4. Post training\u7528\u30c7\u30fc\u30bf\u3068\u8a55\u4fa1\u30eb\u30fc\u30d6\u30ea\u30c3\u30af\u306e\u4f5c\u6210
    \u5408\u6210\u3057\u305f30,000\u4ef6\u306e\u30c7\u30fc\u30bf\u306e\u3046\u306129,600\u4ef6\u3092Post training\u306b\u3001200\u4ef6\u3092training\u4e2d\u306e\u691c\u8a3c\u7528\u306b\u3001200\u4ef6\u3092\u30c6\u30b9\u30c8\u7528\u306b\u5206\u5272\u3057\u305f[5]\u3002\u8a55\u4fa1\u7528\u30c7\u30fc\u30bf\u306b\u306f\u8a55\u4fa1\u30eb\u30fc\u30d6\u30ea\u30c3\u30af\u3092\u5165\u308c\u8fbc\u307fLLM as a judge\u3067\u5224\u5b9a\u3057\u3084\u3059\u304f\u3057\u305f\u3002\u8a55\u4fa1\u30c7\u30fc\u30bf\u306f\u5168\u91cf\u76ee\u691c\u8a3c\u3057\u3066\u3044\u308b[6]\u3002<\/li>\n\n\n\n
  5. Post training\u3068\u8a55\u4fa1
    \u5408\u6210\u3057\u305f\u30c7\u30fc\u30bf\u3092\u7528\u3044\u3066Gemma-2-Llama-Swallow 2B\uff08    https:\/\/swallow-llm.github.io\/gemma2-llama-swallow.ja.html<\/a>\uff09[7]\u3068Gemma 4 E2B\uff08https:\/\/huggingface.co\/google\/gemma-4-E2B<\/a>\uff09[8]\u306b\u5bfe\u3057\u3066fine tuning\u3092\u884c\u3063\u305f\u3002Gemma-2-Llama-Swallow 2B\u3067\u306fFull Fine-Tuning\u3068QLoRA\u3092\u884c\u3044\u3001Gemma 4 E2B\u306fUnsloth LoRA\u3092\u5229\u7528\u3057\u305f\u3002\u6210\u7e3e\u306e\u826f\u304b\u3063\u305fGemma-2-Llama-Swallow 2B + QLoRA\u306b\u5bfe\u3057\u3066\u306fDPO\uff08Direct Preference Optimization\uff09\u3092\u7528\u3044\u305fRL\u3092\u8ffd\u52a0\u7684\u306b\u5b9f\u65bd\u3057\u305f[9]\u3002\u5b66\u7fd2\u74b0\u5883\u306fNVIDIA RTX Pro 6000\u3067\u3042\u308b[10]\u3002
    \u8a55\u4fa1\u306fBLEU\u306a\u3069\u306e\u6a5f\u68b0\u8a55\u4fa1\u306e\u4ed6\u3001GPT-5.5\u3092\u7528\u3044\u305fLLM as a judge\u3067\u884c\u3063\u305f\uff08\u76ee\u691c\u3082\u5b9f\u65bd\u3057\u3066\u3044\u308b\uff09[11]\u3002\u6bd4\u8f03\u5bfe\u8c61\u3068\u3057\u3066Gemma 4 31B\uff08\u898f\u6a21\u304c\u5927\u304d\u304f\u65e5\u672c\u8a9e\u306b\u5f37\u3044\u30ed\u30fc\u30ab\u30eb\u30e2\u30c7\u30eb\uff09\u3068Claude Opus 4.6\uff08\u30d5\u30ed\u30f3\u30c6\u30a3\u30a2\u30e2\u30c7\u30eb\uff09\u3092\u7528\u3044\u305f\u3002\u3053\u308c\u3089\u306f1-shot\u69cb\u6210\u3067Codex\u306b\u3088\u308b\u30d7\u30ed\u30f3\u30d7\u30c8\u30c1\u30e5\u30fc\u30cb\u30f3\u30b0\u3092\u5b9f\u65bd\u3057\u3066\u3044\u308b[12]\u3002<\/li>\n<\/ol>\n\n\n\n

    \u7d50\u679c<\/h2>\n\n\n\n

    \u7d50\u679c\u306f\u4e0b\u8868\u306e\u3068\u304a\u308a\u3002\u6700\u7d42\u30e2\u30c7\u30eb\u306f2B\u306731B\u306eGemma 4\u3092\u8d85\u3048\u3001Opus 4.6\u306b\u8feb\u308b\u6027\u80fd\u3092\u51fa\u305b\u305f[13]\u3002\u307e\u305f\u3001\u6559\u5e2b\u30e2\u30c7\u30eb\u3067\u3042\u308bMistral Large\u3001Deepseek V4 Flash\u5358\u4f53\u306e\u6027\u80fd\u3092\u8d85\u3048\u3066\u304a\u308a\u3001\u53c2\u7167\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306e\u6d3b\u7528\u3084Agentic\u306a\u30c7\u30fc\u30bf\u5408\u6210\u306b\u52b9\u679c\u304c\u3042\u3063\u305f\u3053\u3068\u304c\u3046\u304b\u304c\u3048\u308b\u3002<\/p>\n\n\n\n

    \u30e2\u30c7\u30eb \/ \u624b\u6cd5<\/th>BLEU<\/th>chrF<\/th>LLM as a judge<\/th><\/tr><\/thead>
    \u6b63\u89e3\u30c7\u30fc\u30bf<\/td>100.00<\/td>100.00<\/td>5.00<\/td><\/tr>
    Claude Opus 4.6 \/ 1-shot<\/td>71.54<\/td>75.34<\/td>4.69<\/td><\/tr>
    Gemma-2-Llama-Swallow 2B \/ QLoRA + DPO<\/strong><\/td>77.28<\/strong><\/td>74.56<\/strong><\/td>4.64<\/strong><\/td><\/tr>
    Gemma 4 31B \/ 1-shot<\/td>67.35<\/td>71.73<\/td>4.60<\/td><\/tr>
    Gemma-2-Llama-Swallow 2B \/ QLoRA<\/strong><\/td>79.76<\/strong><\/td>82.37<\/strong><\/td>4.60<\/strong><\/td><\/tr>
    Gemma-2-Llama-Swallow 2B \/ Full FT<\/strong><\/td>79.21<\/strong><\/td>82.00<\/strong><\/td>4.53<\/strong><\/td><\/tr>
    Gemma 4 E2B \/ Unsloth LoRA final<\/strong><\/td>76.37<\/strong><\/td>78.60<\/strong><\/td>4.35<\/strong><\/td><\/tr>
    Mistral Large 2512<\/td>49.69<\/td>51.44<\/td>4.27<\/td><\/tr>
    Deepseek V4 Flash<\/td>52.75<\/td>59.30<\/td>3.84<\/td><\/tr>
    Gemma-2-Llama-Swallow 2B \/ Post training\u524d<\/span><\/td>44.83<\/span><\/td>62.98<\/span><\/td>2.72<\/span><\/td><\/tr>
    Gemma 4 E2B \/ Post training\u524d<\/span><\/td>16.73<\/span><\/td>44.14<\/span><\/td>2.35<\/span><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

    \u203b \u592a\u5b57\u306f\u672c\u4ef6\u3067Post training\u3092\u884c\u3063\u305f\u7d50\u679c\u3002\u4e0b\u7dda\u306fPost training\u524d\u306e\u5024\u3002<\/p>\n\n\n\n

    \u6240\u611f<\/h2>\n\n\n\n

    \u30c7\u30fc\u30bf\u5408\u6210\u306b50 USD\u3001\u6570\u6642\u9593\u306e\u5b66\u7fd2\u3068\u3044\u3046\u898f\u6a21\u3067\u30012B\u306e\u30e2\u30c7\u30eb\u304c\u30d5\u30ed\u30f3\u30c6\u30a3\u30a2\u30e2\u30c7\u30eb\u306eone shot\u306b\u8089\u8584\u3059\u308b\u6027\u80fd\u3068\u306a\u3063\u305f\u306e\u306f\u6b63\u76f4\u9a5a\u304d\u3060\u3063\u305f\u3002\u656c\u8a9e\u5909\u63db\u3068\u3044\u3046\u72ed\u304f\u7279\u5316\u3057\u305f\u30bf\u30b9\u30af\u3067\u3042\u308b\u3068\u306f\u3044\u3048\u3001\u300c\u84b8\u7559\u53ef\u80fd\u306a\u6559\u5e2b\u30e2\u30c7\u30eb\u3067\u5de5\u592b\u3057\u305f\u30c7\u30fc\u30bf\u3092\u5408\u6210\u3057\u3001SLM\u3092Post training\u3059\u308b\u300d\u3068\u3044\u3046\u30ec\u30b7\u30d4\u306e\u8cbb\u7528\u5bfe\u52b9\u679c\u306f\u9ad8\u305d\u3046\u3002<\/p>\n\n\n\n

    Kimi K3\u3084DeepSeek V4 Flash 0731\u306a\u3069\u9ad8\u6027\u80fd\u306a\u5927\u898f\u6a21\u516c\u958b\u30e2\u30c7\u30eb\u304c\u5897\u52a0\u3057\u3066\u3044\u308b\u3001\u84b8\u7559\u53ef\u80fd\u306a\u30e2\u30c7\u30eb\u304c\u5897\u3048\u3066\u304d\u3066\u3044\u308b\u3001SLM\u306e\u6027\u80fd\u304c\u4e0a\u304c\u3063\u3066\u3044\u308b\u3001API\u30b3\u30b9\u30c8\u304c\u9ad8\u304f\u306a\u3063\u3066\u304d\u3066\u3044\u308b\u3001\u2026\u306a\u3069\u306a\u3069\u6700\u8fd1\u306e\u96f0\u56f2\u6c17\u304b\u3089\u3053\u306e\u624b\u306e\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3082\u91cd\u8981\u306b\u306a\u308a\u305d\u3046[14]\u3002<\/p>\n\n\n\n

    \u811a\u6ce8<\/h3>\n\n\n\n

    [1] https:\/\/openrouter.ai\/models?distillable=true<\/a>\u3001Open router\u7684\u306b\u306fdistillable\u3068\u306a\u3063\u3066\u3044\u308bKimi K3\u3084DeepSeek V4\u306b\u3068\u3066\u3082\u671f\u5f85\u304c\u9ad8\u3044\uff08\u5b9f\u614b\u3068\u3057\u3066\u306f\u5229\u7528\u898f\u7d04\u3092\u8981\u78ba\u8a8d\uff09
    [2] Small Language Model\u3001\u30b9\u30e2\u30fc\u30eb\u306e\u5b9a\u7fa9\u306f\u306a\u3093\u3068\u306a\u304f10B\u4ee5\u4e0b\u304f\u3089\u3044\u3060\u3068\u601d\u3046\u304c\u300c10B\u304c\u5c0f\u898f\u6a21\u306a\u306e\u304b\uff1f\u300d\u306f\u8b0e\u3067\u3042\u308b\u3002
    [3] 284B, 13B Active\u306eLLM\u3001MIT\u30e9\u30a4\u30bb\u30f3\u30b9\u3001
    DeepSeek-AI, et al, “DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence,” 2026.
    [4] 675B, 41B Active\u306eLLM\u3001Apache-2 \u30e9\u30a4\u30bb\u30f3\u30b9\u3001
    Mistral AI, “Mistral Large 3 Model Card,” , 2025.
    [5] \u30c7\u30fc\u30bf\u5408\u6210\u3067\u4f7f\u7528\u3057\u305f\u30b3\u30b9\u30c8\u306f50 USD\u7a0b\u5ea6\u3002
    [6] \u656c\u8a9e\u5909\u63db\u306e\u59a5\u5f53\u6027\u306f\u78ba\u8a8d\u3001\u5b66\u7fd2\u30c7\u30fc\u30bf\u3068\u30da\u30eb\u30bd\u30ca\u30fb\u30b3\u30f3\u30c6\u30ad\u30b9\u30c8\u306e\u88ab\u308a\u304c\u306a\u3044\u3053\u3068\u3082\u78ba\u8a8d\u306f\u3057\u3066\u3044\u308b\u304c\u3001\u5408\u6210\u30c7\u30fc\u30bf\u3067\u3042\u308b\u306e\u3067\u305d\u306e\u5206\u5e03\u3068\u306eLeakage\u306f\u907f\u3051\u3089\u308c\u306a\u3044\u3068\u306f\u601d\u3046\u3002
    [7] 2B\u306eSLM\u3001    https:\/\/ai.google.dev\/gemma\/terms<\/a> & Llama3.3\u30e9\u30a4\u30bb\u30f3\u30b9\uff08https:\/\/developer.meta.com\/ai\/llama3_3\/license\/<\/a>\uff09\u306b\u6cbf\u3063\u3066\u5229\u7528\u53ef\u80fd\u3001
    Kazuki Fujii, et al, “Continual Pre-Training for Cross-Lingual LLM Adaptation:Enhancing Japanese Language Capabilities,” in Proceedings of the First Conference on Language Modeling, 2024, pp. (to appear).
    Naoaki Okazaki, et al, “Building a Large Japanese Web Corpus for Large Language Models,” in Proceedings of the First Conference on Language Modeling, 2024, pp. (to appear).
    Youmi Ma, et al, “Building Instruction-Tuning Datasets from Human-Written Instructions with Open-Weight Large Language Models,” 2025.
    [8] \u5b9f\u8cea5.1B\u306eSLM\u3001Apache-2 \u30e9\u30a4\u30bb\u30f3\u30b9\u3001
    Gemma Team, et al, “Gemma 4 Technical Report,” 2026.
    [9] SFT\u6e08\u307fadapter\u3092\u51fa\u767a\u70b9\u306bDPO\u3002\u5f37\u5316\u5b66\u7fd2\u3067\u306f\u3001\u6b63\u89e3\u30e1\u30fc\u30eb\u3092chosen\u3001\u4e8b\u5b9f\u3092\u58ca\u3059\u3001\u656c\u8a9e\u306e\u8aa4\u7528\u3092\u5165\u308c\u308b\u3001\u4f59\u8a08\u306a\u8aac\u660e\u3092\u6df7\u305c\u308b\u3001\u69cb\u9020\u3092\u6b20\u843d\u3055\u305b\u308b\u3001\u3068\u3044\u3063\u305fhard negative\u3092rejected\u3068\u3057\u305f\u3002
    [10] \u30d1\u30e9\u30e1\u30fc\u30bf\u306b\u3082\u3088\u308b\u306e\u3060\u308d\u3046\u304c\u3001\u9577\u304f\u3066\u3082\u6570\u6642\u9593\u3067\u5b9f\u884c\u53ef\u80fd\u3002SFT\u306e\u307f\u3067\u3082\u304b\u306a\u308a\u306e\u52b9\u679c\u304c\u3042\u3063\u305f\u305f\u3081RL\u306f\u6700\u7d42\u8abf\u6574\u3068\u3057\u3066\u5b9f\u65bd\u3057\u3066\u3044\u308b\u3002
    [11] \u30c7\u30fc\u30bf\u5408\u6210\u6642\u306b    \u300c\u656c\u8a9e\u306e\u6307\u91dd\u300d<\/a>\u3092\u7528\u3044\u8a55\u4fa1\u30eb\u30fc\u30d6\u30ea\u30c3\u30af\u3092\u4f5c\u6210\u3057\u3066\u3044\u308b\u305f\u3081\u3001LLM as a judge\u3068\u76ee\u691c\u306f\u307b\u3068\u3093\u3069\u6574\u5408\u3057\u3066\u3044\u305f\u3002
    [12] \u691c\u8a3c\u6642\u70b9\u3067\u6027\u80fd\u306e\u826f\u3044\u3082\u306e\u3068\u3057\u3066\u6d3b\u7528\u3002Judge\u304cGPT-5.5\u3067\u3042\u308b\u305f\u3081\u3001Family\u30d0\u30a4\u30a2\u30b9\u3092\u907f\u3051\u308b\u305f\u3081OpenAI\u7cfb\u5217\u3067\u306f\u306a\u3044\u3082\u306e\u3092\u4f7f\u3063\u3066\u3044\u308b\u3002
    [13] Gemma-2-Llama-Swallow 2B\u306f\u3068\u3066\u3082\u6027\u80fd\u304c\u9ad8\u3044\u3002\u65e5\u672c\u8a9e\u3067\u306e\u7d99\u7d9a\u5b66\u7fd2\u7b49\u304c\u52b9\u679c\u3092\u767a\u63ee\u3057\u3066\u3044\u308b\u3088\u3046\u306b\u898b\u3048\u308b\uff08\u3053\u306e\u30bf\u30b9\u30af\u3068\u306e\u76f8\u6027\u3082\u3088\u3055\u305d\u3046\u306b\u601d\u3048\u308b\uff09\u3002\u9069\u5f53\u306a\u30c7\u30fc\u30bf\u3092\u5165\u308c\u3066\u307f\u305f\u611f\u3058\u306e\u52d5\u4f5c\u3082\u60aa\u304f\u306a\u3055\u305d\u3046\u306a\u306e\u3067\u3001\u5b9f\u30c7\u30fc\u30bf\u3092\u4f7f\u3063\u305f\u691c\u8a3c\u3092\u3057\u3066\u307f\u305f\u3044\u3068\u3053\u308d\u3002\u624b\u4f5c\u6210\u30c7\u30fc\u30bf\u3067\u3057\u3063\u304b\u308a\u691c\u8a3c\u3057\u305f\u3044\u6c17\u6301\u3061\u3082\u306a\u304f\u306f\u306a\u3044\u304c\u3001\u3077\u308b\u30fc\u3075\u304a\u3076\u3053\u3093\u305b\u3077\u3068\u3068\u3057\u3066\u306f\u3044\u3063\u305f\u3093\u3053\u306e\u7d50\u679c\u3067\u826f\u3044\u304b\u306a\u3068\u601d\u3063\u3066\u3044\u308b\u3002\uff08\u5408\u6210\u30c7\u30fc\u30bf\u306e\u9650\u754c\u3068Leakage\u7591\u3044\u306f\u907f\u3051\u3089\u308c\u306a\u3044\u306e\u3067\u30b9\u30b3\u30a2\u306e\u8a55\u4fa1\u306f\u8a87\u5927\u5e83\u544a\u6c17\u5473\u3067\u3042\u308b\uff09
    [14] \u5b9f\u969b\u306e\u3068\u3053\u308d\u306f\u826f\u304f\u308f\u304b\u3089\u306a\u3044\u304c\u3001\u3046\u307e\u304f\u30c7\u30fc\u30bf\u5408\u6210\u3057\u3066\u4f7f\u3048\u308bSLM\u3092\u4f5c\u308b\u3068\u3044\u3046\u65b9\u5411\u6027\u306f\u60aa\u304f\u306a\u3055\u305d\u3046\u306a\u4e88\u611f\u3002
    <\/p>\n","protected":false},"excerpt":{"rendered":"

    \u6700\u8fd1\u3001\u84b8\u7559\u304c\u53ef\u80fd\u306a\u5927\u898f\u6a21\u30e2\u30c7\u30eb\u304c\u5897\u52a0\u3057\u3066\u3044\u308b[1] \u3002\u656c\u8a9e\u5909\u63db\u3092\u5bfe\u8c61\u306bSLM[2]\u3092Post trainig\u3059\u308b\u3053\u3068\u3067\u5b9f\u7528\u7684\u306a\u30e2\u30c7\u30eb\u304c\u69cb\u7bc9\u53ef\u80fd\u304b\u8a66\u3057\u3066\u307f\u305f\u3002\u7d50\u679c\u3001Post training\u5f8c\u306e2B\u306e\u30e2\u30c7\u30eb\uff08Gemma-2 … “\u5c0f\u578b\u8a00\u8a9e\u30e2\u30c7\u30eb\uff08SLM\uff09\u306ePost training” \u306e<\/span>\u7d9a\u304d\u3092\u8aad\u3080<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[85],"class_list":["post-1244","post","type-post","status-publish","format-standard","hentry","category-ai","tag-85"],"_links":{"self":[{"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/1244","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1244"}],"version-history":[{"count":32,"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/1244\/revisions"}],"predecessor-version":[{"id":1278,"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/1244\/revisions\/1278"}],"wp:attachment":[{"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1244"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1244"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/staka.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1244"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}