Beyond Jupyter is a collection of self-study materials on software design, with a specific focus on machine learning applications, which demonstrates how sound software design can accelerate both development and experimentation. The software being developed in machine learning contexts often remains at fairly low levels of abstraction and fails to satisfy well-established standards in software des
Swallow on mistral Mistral 7BおよびMixtral 8x7Bの日本語能力を強化した大規模言語モデル (Swallow-MS 7B, Swallow-MX 8x7B) です。Apache 2.0の寛容なライセンスでモデルのパラメータ(重み)を公開していますので、研究やビジネスに活用できます。 View on HuggingFace 大規模言語モデルSwallow-MS 7BおよびSwallow-MX 8x7Bは、東京工業大学情報理工学院の岡崎研究室と横田研究室、国立研究開発法人産業技術総合研究所の研究チームで開発された大規模言語モデルです。英語の言語理解や対話で高い能力を持つ大規模言語モデルMistral 7BおよびMixtral 8x7Bの日本語能力を強化するため、研究チームは日本語の大規模な言語データを用いて継続事前学習を行いました。研究チームで実施した性能評
I will never forget being at TI7 where OpenAI revealed an AI that could take on pro Dota players. Dota is an insanely complicated and difficult game. This was an eye opening moment for me that led to a career shift.https://en.wikipedia.org/wiki/OpenAI_Five The caveat being that the scope of the game was significantly pared down for the sake of the AI. Specifically the team compositions were pre-de
Thanks for posting that, I thought it was a great read (as someone who last used C++ probably about 25 years ago...)Given that so many of the criticisms were about C++ being over-complicated, I do worry about languages just becoming more and more difficult over time as everyone wants their pet feature added, but due to backwards-compatibility concerns old/obsolete features are rarely removed. For
We introduce the Yi model family, a series of language and multimodal models that demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and 34B pretrained language models, then we extend them to chat models, 200K long context models, depth-upscaled models, and vision-language models. Our base models achieve strong performance on a wide range of benchmarks like MMLU,
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