[B! NLP] serihiroã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

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NLPã«é–¢ã™ã‚‹serihiroã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (64)

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ã¯ã˜ã‚ã¦ã®è‡ªç„¶è¨€èªžå‡¦ç† | ã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆã®åºƒå ´
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serihiro 2024/09/04
NLP
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GitHub - google/sentencepiece: Unsupervised text tokenizer for Neural Network-based text generation.
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serihiro 2024/08/30
NLP
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NLPã‚³ãƒã‚ã‚¦ãƒ
NLPã‚³ãƒã‚ã‚¦ãƒ ã¯è‡ªç„¶è¨€èªžå‡¦ç† (NLP) ãŠã‚ˆã³ è¨ˆç®—è¨€èªžå¦ (CL) ã«é–¢é€£ã™ã‚‹å¹…åºƒã„åˆ†é‡Žã§æœ€å…ˆç«¯ã®ç ”ç©¶ãƒ»é–‹ç™ºã«å–ã‚Šçµ„ã‚“ã§ã„ã‚‹æ–¹ã‚’ãŠæ‹›ãã™ã‚‹ã‚ªãƒ³ãƒ©ã‚¤ãƒ³ã®ãƒˆãƒ¼ã‚¯ã‚¤ãƒ™ãƒ³ãƒˆã§ã™ã€‚ç ”ç©¶ã«é–¢ã™ã‚‹è°è«–ã¨äº¤æµã‚’é€šã˜ã¦æ—¥æœ¬äººãƒ»æ—¥æœ¬èªžNLPã‚³ãƒŸãƒ¥ãƒ‹ãƒ†ã‚£ãƒ¼ã®ãƒ—ãƒ¬ã‚¼ãƒ³ã‚¹ã‚’å‘ä¸Šã•ã›ã‚‹ã“ã¨ã‚’ç›®çš„ã¨ã—ã¦ã„ã¾ã™ã€‚
serihiro 2023/12/07
NLP
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è¨€èªžå‡¦ç†å¦ä¼šç¬¬30å›žå¹´æ¬¡å¤§ä¼š(NLP2024)
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serihiro 2023/12/07
NLP
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GitHub - yahoojapan/JGLUE: JGLUE: Japanese General Language Understanding Evaluation
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serihiro 2023/11/14
NLP

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serihiro 2023/10/07
tutorial

NLP

search
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serihiro 2023/10/07
NLP

tutorial

search
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è¨€èªžå‡¦ç†ã§ã‚ˆãä½¿ã†å‰å‡¦ç†ã¾ã¨ã‚ -tokenize, subword- - æ–‡ç³»ã¨ç†ç³»ã®äº¤å·®ç‚¹
è¨€èªžå‡¦ç†ã‚’è¡Œã†ã¨ãã®åŸºæœ¬ã¨ã—ã¦ï¼Œç¾åœ¨ã¯æ–‡ç« ã‚’å˜èªžãªã©ã®ä½•ã‚‰ã‹ã®å˜ä½ã«åŒºåˆ‡ã‚Šï¼ˆãƒˆãƒ¼ã‚¯ãƒŠã‚¤ã‚º (tokenize) ã—ã¦ï¼‰ï¼Œãã‚Œã‚‰ã‚’ãƒ™ã‚¯ãƒˆãƒ«ã«è½ã¨ã—è¾¼ã‚“ã§ãƒ¢ãƒ‡ãƒ«ã§å‡¦ç†ã™ã‚‹ã“ã¨ãŒå¤šã„ã§ã™ï¼Ž ä»Šå›žã¯ãƒˆãƒ¼ã‚¯ãƒŠã‚¤ã‚ºï¼ˆå˜èªžã‚’åŒºåˆ‡ã‚‹ã“ã¨ï¼‰ã«ãƒ•ã‚©ãƒ¼ã‚«ã‚¹ã—ã¦ï¼Œãã‚Œã‚’ã§ã©ã®æ§˜ã«æ›¸ãã‹ã‚’ç°¡å˜ã«ã”ç´¹ä»‹ã—ã¾ã™ï¼Žè¨€èªžã¯ä¸»ã« python ã‚’ä½¿ç”¨ã—ã¾ã™ï¼Ž ç›®æ¬¡ ãƒˆãƒ¼ã‚¯ãƒŠã‚¤ã‚º æ—¥æœ¬èªžã®å ´åˆ è‹±èªžã®å ´åˆ ã‚µãƒ–ãƒ¯ãƒ¼ãƒ‰ (Subword) BPE (Bite Pair Encoding) SentencePiece å‚è€ƒ ãƒˆãƒ¼ã‚¯ãƒŠã‚¤ã‚º ãã‚‚ãã‚‚ãƒˆãƒ¼ã‚¯ãƒŠã‚¤ã‚ºã¨ã¯ï¼Œå˜èªžã‚’ãƒˆãƒ¼ã‚¯ãƒ³ã¨ã„ã†å˜ä½ã«åŒºåˆ‡ã‚‹ã“ã¨ã‚’æŒ‡ã—ã¾ã™ãŒï¼Œã“ã®åŒºåˆ‡ã‚Šæ–¹ã¯æ§˜ã€…ã‚ã‚Šã¾ã™ï¼Žã‚ˆãä½¿ã‚ã‚Œã‚‹ã®ã¯å˜èªžã‚„å½¢æ…‹ç´ ã§ã™ï¼Ž ã•ã‚‰ã«å¾Œã»ã©èª¬æ˜Žã™ã‚‹ã‚µãƒ–ãƒ¯ãƒ¼ãƒ‰ (subword) ã¨ã„ã£ã¦ï¼Œå˜èªžã‚’ã•ã‚‰ã«ç´°ã‹ãåŒºåˆ‡ã£ãŸè¡¨ç¾ã‚’ãƒˆãƒ¼ã‚¯ãƒ³ã¨ã—ã¦æ‰±ã†ã“ã¨ã‚„ï¼Œï¼‘æ–‡å—ã‚’ï¼‘ãƒˆãƒ¼ã‚¯ãƒ³ã¨ã—ã¦åˆ†å‰²ã™ã‚‹ã“ã¨ï¼ˆ
serihiro 2023/04/29
NLP
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NLTK :: Natural Language Toolkit
Natural Language ToolkitÂ¶ NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an ac
serihiro 2023/04/29
NLP
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ã€å®Œå…¨ä¿å˜ç‰ˆã€‘GPT ã‚’ç‰¹å®šã®ç›®çš„ã«ç‰¹åŒ–ã•ã›ã¦æ‰±ã† (Fine-tuning, Prompt, Index, etc.) - Qiita
ã€å®Œå…¨ä¿å˜ç‰ˆã€‘GPT ã‚’ç‰¹å®šã®ç›®çš„ã«ç‰¹åŒ–ã•ã›ã¦æ‰±ã† (Fine-tuning, Prompt, Index, etc.)OpenAI ChatGPTlangchainGPT-4LlamaIndex ç”ŸæˆAIã‚«ãƒ³ãƒ•ã‚¡ãƒ¬ãƒ³ã‚¹ ã€œå¾¹åº•è§£å‰–ã€Œãƒˆãƒƒãƒ—ãƒ©ãƒ³ãƒŠãƒ¼ã‹ã‚‰è¦‹ãŸæ—¥æœ¬ãŒæŒ‘ã‚€ç”ŸæˆAIã®æœ€å‰ç·šã€ã€œ æ—¥æ™‚ï¼š5æœˆ8æ—¥(æ°´) 10:00-18:30 å½¢å¼ï¼šã‚ªãƒ•ãƒ©ã‚¤ãƒ³ãƒ»ã‚ªãƒ³ãƒ©ã‚¤ãƒ³ã®ãƒã‚¤ãƒ–ãƒªãƒƒãƒ‰é–‹å‚¬ å ´æ‰€ï¼šæ±äº¬å¤§å¦ä¼Šè—¤è¬æ©ãƒ›ãƒ¼ãƒ«ï¼ˆã‚ªãƒ³ãƒ©ã‚¤ãƒ³å‚åŠ ã®æ–¹ã¯é…ä¿¡URLã‚’ãŠé€ã‚Šã—ã¾ã™ï¼‰ å‚åŠ æ–¹æ³•ï¼šä¸‹è¨˜ã‚¤ãƒ™ãƒ³ãƒˆãƒšãƒ¼ã‚¸ã‚ˆã‚Šç”³è¾¼ ChatGPT ã«ä»£è¡¨ã•ã‚Œã‚‹ä»Šæ—¥ã® AI ãƒ–ãƒ¼ãƒ ã‚’ç‰½å¼•ã—ã¦ã„ã‚‹ã®ã¯ å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«ï¼ˆLarge-scale Language Model, LLMï¼‰ ã¨è¨€ã£ã¦ã‚‚éŽè¨€ã§ã¯ãªã„ã§ã—ã‚‡ã†ã€‚LLM ã¨ã¯å¤§é‡ã®ãƒ†ã‚ã‚¹ãƒˆãƒ‡ãƒ¼ã‚¿ã‚’ä½¿ã£ã¦ãƒˆãƒ¬ãƒ¼ãƒ‹ãƒ³ã‚°ã•ã‚ŒãŸè‡ªç„¶è¨€èªžå‡¦ç†ã®ãƒ¢ãƒ‡ãƒ«ã§ã€ä»£è¡¨çš„ãªã‚‚ã®ã«ã€GPTï¼ˆOpenAIï¼‰
serihiro 2023/03/31
LLM

NLP

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serihiro 2023/03/31
LLM

NLP
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Wikipediaã®æ—¥æœ¬èªžã‚³ãƒ¼ãƒ‘ã‚¹ã®æº–å‚™ï½œnpaka
Wikipediaã®æ—¥æœ¬èªžã‚³ãƒ¼ãƒ‘ã‚¹ã‚’æº–å‚™ã™ã‚‹æ–¹æ³•ã‚’ã¾ã¨ã‚ã¾ã—ãŸã€‚ 1. Wikipediaãƒ€ãƒ³ãƒ—ãƒ•ã‚¡ã‚¤ãƒ«ã®å–å¾—ã¯ã˜ã‚ã«ã€https://dumps.wikimedia.org/jawiki/latest/ ã‹ã‚‰ã€Wikipediaã®æ—¥æœ¬èªžã®ãƒ€ãƒ³ãƒ—ãƒ•ã‚¡ã‚¤ãƒ«ã€Œjawiki-latest-pages-articles.xml.bz2ã€ã‚’ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ãŠã‚ˆã³è§£å‡ã—ã¾ã™ã€‚ ãƒ»è§£å‡å‰ : jawiki-latest-pages-articles.xml.bz2 (3.2GB) ãƒ»è§£å‡å¾Œ : jawiki-latest-pages-articles.xml : (13.47GB) 2. Wikipediaã®æ—¥æœ¬èªžã‚³ãƒ¼ãƒ‘ã‚¹ã®ä½œæˆ Wikipediaã®ãƒ€ãƒ³ãƒ—ãƒ•ã‚¡ã‚¤ãƒ«ã¯XMLå½¢å¼ãªã®ã§ã€è¨˜äº‹ã‚’æŠ½å‡ºã™ã‚‹ãƒ„ãƒ¼ãƒ« ã€ŒWikiExtractorã€ã‚’ä½¿ã£ã¦ã€XMLã‚¿ã‚°ã‚’å‰Šé™¤ã—ã¾ã™ã€‚ (1) Anacondaã§Python
serihiro 2023/03/29
NLP
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è‡ªåˆ†ã®Tweetã‚’ä½¿ã£ã¦Sentencepieceã¨MeCabã®åˆ†ã‹ã¡æ›¸ãã®æ¯”è¼ƒã‚’è¡Œã† - Sansan Tech Blog
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serihiro 2023/03/29
NLP
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2022å¹´11æœˆã«Open AIãŒå…¬é–‹ã—ãŸChatGPTãŒä¸–ç•Œã§æ³¨ç›®ã‚’é›†ã‚ã¦ã„ã‚‹ã€‚ä¸€èˆ¬ãƒ‰ãƒ¡ã‚¤ãƒ³ã‹ã¤å¤šè¨€èªžã§ã€å¾“æ¥ã®ãƒãƒ£ãƒƒãƒˆãƒœãƒƒãƒˆã¨ã¯ãƒ¬ãƒ™ãƒ«ã®ç•°ãªã‚‹é«˜å“è³ªã®å¯¾è©±ã‚’ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ã«å®Ÿç¾ã™ã‚‹ã‚µãƒ¼ãƒ“ã‚¹ã‚’ï¼ˆResearch Previewç‰ˆã§ã¯ã‚ã‚‹ãŒï¼‰ç„¡æ–™ã§æä¾›ã—ã€æ¤œç´¢ã€é‡‘èžã€åºƒå‘Šã€æ•™è‚²ã€æ³•å‹™ãªã©ã®åºƒç¯„å›²ãªåˆ†é‡Žã®è»¢â€¦
serihiro 2023/03/29
LLM

NLP
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APE
Large Language Models Are Human-Level Prompt EngineersICLR 2023Yongchao Zhou*, Andrei Ioan Muresanu*, Ziwen Han*, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba[ ArXiv | GitHub | Colab Â | Demo ] By conditioning on natural language instructions, large language models (LLMs) have displayed impressive capabilities as general-purpose computers. However, task performance depends significantly on th
serihiro 2023/03/27
paper

NLP
ãƒªãƒ³ã‚¯
æ—¥æœ¬èªžAlpacaãƒ‡ãƒ¼ã‚¿ã‚’ç”¨ã„ã¦Japanese-Alpaca-LoRAã‚’ä½œã£ãŸã®ã§å…¬é–‹ã—ã¾ã™ã€æœŸé–“é™å®šãƒ‡ãƒ¢ãƒšãƒ¼ã‚¸ã‚ã‚Šã€‘ï½œkun1emon
âš ï¸æ³¨æ„ä»Šå›žå…¬é–‹ã™ã‚‹ã®ã¯LoRAã‚’ç”¨ã„ã¦ä½œæˆã—ãŸLLaMAã®æ—¥æœ¬èªžåŒ–Adapterã§ã‚ã‚Šãƒ¢ãƒ‡ãƒ«è‡ªä½“ã§ã¯ã‚ã‚Šã¾ã›ã‚“ã€‚ LoRAã‚’ãƒžãƒ¼ã‚¸ã™ã‚‹ãƒ™ãƒ¼ã‚¹ã®LLaMAã¯å•†ç”¨ä¸å¯ã§ã‚ã‚Šã€ä»Šå›žå…¬é–‹ã™ã‚‹Adapterã§æ—¥æœ¬èªžåŒ–ã—ãŸãƒ¢ãƒ‡ãƒ«ã‚‚å•†ç”¨åˆ©ç”¨ã¯ã§ãã¾ã›ã‚“ã€‚ OpneAIã®åˆ©ç”¨è¦ç´„ã§ã€OpenAIã‚µãƒ¼ãƒ“ã‚¹ã€ChatGPTã®å‡ºåŠ›çµæžœã‚’ç«¶åˆãƒ¢ãƒ‡ãƒ«é–‹ç™ºç”¨é€”ã«åˆ©ç”¨ã™ã‚‹ã“ã¨ã¯ã§ãã¾ã›ã‚“ ã‚³ãƒ³ãƒ†ãƒ³ãƒ„ç”Ÿæˆè€…ã¯ã§ãã¾ã›ã‚“ã€‚ è©³ç´°ã¯è¨˜äº‹å¾ŒåŠã§è¿°ã¹ã¦ã„ã¾ã™ãŒåˆ©ç”¨è¦ç´„ãŒé©ç”¨ã•ã‚Œã‚‹ã®ã¯ã‚³ãƒ³ãƒ†ãƒ³ãƒ„ç”Ÿæˆè€…ã¾ã§ã§ã™ã€‚ æ¦‚è¦2022å¹´ã®11æœˆæœ«ã«OpenAIã‹ã‚‰ChatGPTãŒç™ºè¡¨ã•ã‚Œã¦ã‹ã‚‰ã€ãã‚Œã«è¿½éšã™ã‚‹ã‚ˆã†ã«Googleã‹ã‚‰Bardã€Metaã‹ã‚‰LLaMAãªã©å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«ï¼ˆLLMï¼‰ãŒç™ºè¡¨ã•ã‚Œã¾ã—ãŸã€‚ã•ã‚‰ã«LLaMA 7Bã‚’ã€Œtext-davinci-003ã€ã‚’ç”¨ã„ã¦ã€ŒSelf-Instructã€ã§ä½œæˆã•ã‚ŒãŸ52Kã®ãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆï¼ˆ
serihiro 2023/03/27
NLP

LLM
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GitHub - BlinkDL/RWKV-LM: RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "inf
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serihiro 2023/03/24
RNN

NLP
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æ—¥æœ¬èªž Wikipedia ã‚¨ãƒ³ãƒ†ã‚£ãƒ†ã‚£ãƒ™ã‚¯ãƒˆãƒ«
ãŠçŸ¥ã‚‰ã› (2018/09/24) æœ€æ–°ç‰ˆã®è¨“ç·´æ¸ˆã¿ãƒ™ã‚¯ãƒˆãƒ«ã¨è¨“ç·´ç”¨ã®ã‚¹ã‚¯ãƒªãƒ—ãƒˆã¯ GitHub ã§å…¬é–‹ã—ã¦ã„ã¾ã™ã€‚ æ¦‚è¦ ã€Œæ—¥æœ¬èªž Wikipedia ã‚¨ãƒ³ãƒ†ã‚£ãƒ†ã‚£ãƒ™ã‚¯ãƒˆãƒ«ã€ã¯ã€æ—¥æœ¬èªžç‰ˆ Wikipedia ã®æœ¬æ–‡å…¨æ–‡ã‹ã‚‰å¦ç¿’ã—ãŸã€å˜èªžã€ãŠã‚ˆã³ Wikipedia ã§è¨˜äº‹ã¨ãªã£ã¦ã„ã‚‹ã‚¨ãƒ³ãƒ†ã‚£ãƒ†ã‚£ã®åˆ†æ•£è¡¨ç¾ãƒ™ã‚¯ãƒˆãƒ«ã§ã™ã€‚Wikipedia ã®è¨˜äº‹æœ¬æ–‡ã®æŠ½å‡ºã«ã¯ WikiExtractor ã‚’ã€å˜èªžåˆ†å‰²ã«ã¯ MeCab ã‚’ã€å˜èªžãƒ™ã‚¯ãƒˆãƒ«ã®å¦ç¿’ã«ã¯ word2vec ã‚’ãã‚Œãžã‚Œç”¨ã„ã¦ã„ã¾ã™ã€‚ ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ 20170201.tar.bz2 (2017å¹´2æœˆ1æ—¥ç‰ˆ, 1.3GB, è§£å‡å¾Œ 2.6GB) 20161101.tar.bz2 (2016å¹´11æœˆ1æ—¥ç‰ˆ, 1.3GB, è§£å‡å¾Œ 2.6GB) ãƒã‚¤ãƒŠãƒªãƒ•ã‚¡ã‚¤ãƒ« (entity_vector.model.bin) ã¨ãƒ†ã‚ã‚¹ãƒˆãƒ•ã‚¡ã‚¤ãƒ« (ent
serihiro 2023/03/23
NLP
ãƒªãƒ³ã‚¯
Alpaca-loraã‚’æ—¥æœ¬èªžã‚¿ã‚¹ã‚¯ã§ãƒ•ã‚¡ã‚¤ãƒ³ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°ã™ã‚‹ - Qiita
Alpaca-LoRAã¨ã„ã†å®¶åºç”¨GPUã§ã‚‚å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«ã®FineTuningãŒå¯èƒ½ãªãƒ¢ãƒ‡ãƒ«ãŒç™ºè¡¨ã•ã‚Œã¾ã—ãŸã€‚ æœ¬è¨˜äº‹ã§ã¯ã€livedoorãƒ‹ãƒ¥ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‘ã‚¹ã‚’ä½¿ç”¨ã—ã¦Alpaca-LoRAã‚’FineTuningã—ã¦ãƒ‹ãƒ¥ãƒ¼ã‚¹ã®ã‚¿ã‚¤ãƒˆãƒ«ã‚’è€ƒãˆã•ã›ã‚‹ã¨ã„ã†ã‚¿ã‚¹ã‚¯ã«æŒ‘æˆ¦ã—ã¦ã¿ã¾ã™ã€‚ æŠ€è¡“ã®æ¦‚è¦ Alpacaã¨ã¯ Alpacaã¨ã¯ã€å…ˆæ—¥MetaãŒç™ºè¡¨ã—ãŸLLaMa 7Bã‚’text-davinci-003ã«ã‚ˆã‚‹self-instructã§ç”Ÿæˆã•ã‚ŒãŸãƒ‡ãƒ¼ã‚¿ã‚’ä½¿ç”¨ã—ã¦FineTuningã—ãŸè¨€èªžãƒ¢ãƒ‡ãƒ«ã€‚ ç”Ÿæˆã—ãŸãƒ‡ãƒ¼ã‚¿ã¯52Kå€‹ã§ç”Ÿæˆã‚³ã‚¹ãƒˆã¯500ãƒ‰ãƒ«ä»¥ä¸‹ã¨ä½Žã‚³ã‚¹ãƒˆã§ã™ã€‚ äººé–“ã«ã‚ˆã‚‹äºˆå‚™è©•ä¾¡ã§ã¯7Bã¨ã„ã†æ¯”è¼ƒçš„å°ã•ãªãƒ¢ãƒ‡ãƒ«ã«ã‚‚é–¢ã‚ã‚‰ãšã€text-davinci-003ã«ä¼¼ãŸæŒ™å‹•ã‚’ç¤ºã™ã¨ã„ã†å ±å‘ŠãŒã‚ã’ã‚‰ã‚Œã¦ã„ã¾ã™ã€‚ Alpaca-LoRAã¨ã¯ Alpaca-LoRAã¨ã¯Alpacaã§ä½œæˆã—ãŸãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆ
serihiro 2023/03/23
NLP

Alpaca
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Alpaca ã¾ã¨ã‚ï½œnpaka
ã€ŒAlpacaã€ã®å¦ç¿’æ–¹æ³•ã«ã¤ã„ã¦è»½ãã¾ã¨ã‚ã¾ã—ãŸã€‚ 1. Alpacaã€ŒAlpacaã€ã¯ã€ã€ŒLLaMA 7Bã€(Meta)ã‚’ãƒ•ã‚¡ã‚¤ãƒ³ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°ã—ãŸè¨€èªžãƒ¢ãƒ‡ãƒ«ã§ã™ã€‚ã€Œtext-davinci-003ã€ã«ã‚ˆã‚‹ã€Œself-instructã€ã§ç”Ÿæˆã•ã‚ŒãŸ52Kã®å‘½ä»¤è¿½å¾“åž‹ã®å¦ç¿’ãƒ‡ãƒ¼ã‚¿ã‚’ä½¿ã£ã¦å¦ç¿’ã—ã¦ã„ã¾ã™ã€‚ã€ŒAlpacaã€ã¯OpenAIã®ã€Œtext-davinci-003ã€ã«ä¼¼ãŸæŒ™å‹•ã‚’ç¤ºã—ã¾ã™ãŒã€é©šãã»ã©å°ã•ãå†ç¾ãŒå®¹æ˜“ã§å®‰ä¾¡ã§ã‚ã‚‹ã“ã¨ãŒç‰¹å¾´ã§ã™ã€‚ ã¾ãŸã€ã€ŒAlpacaã€ã¯å¦è¡“ç ”ç©¶ã®ã¿ã‚’ç›®çš„ã¨ã—ã¦ãŠã‚Šã€å•†ç”¨åˆ©ç”¨ã¯ç¦æ¢ã—ã¦ã„ã¾ã™ã€‚ 2. å¦ç¿’æ¸ˆã¿è¨€èªžãƒ¢ãƒ‡ãƒ« ã¨ å¦ç¿’ãƒ‡ãƒ¼ã‚¿ã‚¢ã‚«ãƒ‡ãƒŸãƒƒã‚¯ãªäºˆç®—ã§é«˜å“è³ªãªè¨€èªžãƒ¢ãƒ‡ãƒ«ã‚’å¦ç¿’ã•ã›ã‚‹ãŸã‚ã«ã¯ã€ã€Œå¼·åŠ›ãªå¦ç¿’æ¸ˆã¿è¨€èªžãƒ¢ãƒ‡ãƒ«ã€ã¨ã€Œé«˜å“è³ªãªå¦ç¿’ãƒ‡ãƒ¼ã‚¿ã€ãŒå¿…è¦ã§ã™ã€‚ 1ã¤ç›®ã¯ã€æœ€è¿‘ãƒªãƒªãƒ¼ã‚¹ã•ã‚ŒãŸMetaã®ã€ŒLLaMAã€ã§è§£æ±ºã•ã‚Œã¾ã™ã€‚2ã¤ç›®ã¯ã€ã€Œself-instru
serihiro 2023/03/23
NLP

LLM
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