How To Revive Deepseek > 자유게시판

• 목록
• 답변
• 글쓰기
• 게시판 리스트 옵션
  • 수정
  • 삭제

DeepSeek 모델은 처음 2023년 하반기에 출시된 후에 빠르게 AI 커뮤니티의 많은 관심을 받으면서 유명세를 탄 편이라고 할 수 있는데요. 허깅페이스 기준으로 지금까지 DeepSeek이 출시한 모델이 48개인데, 2023년 DeepSeek과 비슷한 시기에 설립된 미스트랄AI가 총 15개의 모델을 내놓았고, 2019년에 설립된 독일의 알레프 알파가 6개 모델을 내놓았거든요. 처음에는 Llama 2를 기반으로 다양한 벤치마크에서 주요 모델들을 고르게 앞서나가겠다는 목표로 모델을 개발, 개선하기 시작했습니다. 이렇게 한 번 고르게 높은 성능을 보이는 모델로 기반을 만들어놓은 후, 아주 빠르게 새로운 모델, 개선된 버전을 내놓기 시작했습니다. AI 학계와 업계를 선도하는 미국의 그늘에 가려 아주 큰 관심을 받지는 못하고 있는 것으로 보이지만, 분명한 것은 생성형 AI의 혁신에 중국도 강력한 연구와 스타트업 생태계를 바탕으로 그 역할을 계속해서 확대하고 있고, 특히 중국의 연구자, 개발자, 그리고 스타트업들은 ‘나름의’ 어려운 환경에도 불구하고, ‘모방하는 중국’이라는 통념에 도전하고 있다는 겁니다. DeepSeek의 오픈소스 모델 DeepSeek-V2, 그리고 deepseek ai china-Coder-V2 모델은 독자적인 ‘어텐션 메커니즘’과 ‘MoE 기법’을 개발, 활용해서 LLM의 성능을 효율적으로 향상시킨 결과물로 평가받고 있고, 특히 DeepSeek-Coder-V2는 현재 기준 가장 강력한 오픈소스 코딩 모델 중 하나로 알려져 있습니다. 특히, DeepSeek만의 혁신적인 MoE 기법, 그리고 MLA (Multi-Head Latent Attention) 구조를 통해서 높은 성능과 효율을 동시에 잡아, 향후 주시할 만한 AI 모델 개발의 사례로 인식되고 있습니다.

The 7B model uses Multi-Head attention (MHA) while the 67B mannequin makes use of Grouped-Query Attention (GQA). Ethical concerns and limitations: While DeepSeek-V2.5 represents a major technological development, it additionally raises necessary ethical questions. To run domestically, DeepSeek-V2.5 requires BF16 format setup with 80GB GPUs, with optimal performance achieved utilizing 8 GPUs. LLM v0.6.6 helps DeepSeek-V3 inference for FP8 and BF16 modes on each NVIDIA and AMD GPUs. Although the export controls were first launched in 2022, they only began to have a real impact in October 2023, and the newest technology of Nvidia chips has only recently begun to ship to information centers. Hasn’t the United States restricted the variety of Nvidia chips offered to China? The licensing restrictions reflect a growing awareness of the potential misuse of AI applied sciences. The open-source nature of DeepSeek-V2.5 might accelerate innovation and democratize access to superior AI applied sciences. DeepSeek-V2.5 was launched on September 6, 2024, and is accessible on Hugging Face with each internet and API access. DeepSeek V3 is monumental in measurement: 671 billion parameters, or 685 billion on AI dev platform Hugging Face.

Meta announced in mid-January that it would spend as much as $sixty five billion this yr on AI growth. It’s been just a half of a year and DeepSeek AI startup already considerably enhanced their fashions. Its performance in benchmarks and third-party evaluations positions it as a powerful competitor to proprietary fashions. It could stress proprietary AI companies to innovate additional or reconsider their closed-supply approaches. This is all nice to hear, although that doesn’t mean the large companies on the market aren’t massively rising their datacenter funding within the meantime. There are plenty of frameworks for building AI pipelines, but when I want to combine manufacturing-ready end-to-end search pipelines into my software, Haystack is my go-to. Why this issues - the place e/acc and true accelerationism differ: e/accs assume humans have a vivid future and are principal brokers in it - and anything that stands in the way in which of humans utilizing expertise is dangerous. I think I'll make some little undertaking and document it on the monthly or weekly devlogs until I get a job. But we could make you've gotten experiences that approximate this.

Aider can hook up with virtually any LLM. Aider helps you to pair program with LLMs to edit code in your local git repository Start a new challenge or work with an existing git repo. The model is optimized for both large-scale inference and small-batch local deployment, enhancing its versatility. The model is optimized for writing, instruction-following, and coding tasks, introducing function calling capabilities for exterior instrument interaction. The model’s mixture of basic language processing and coding capabilities sets a new customary for open-source LLMs. Breakthrough in open-source AI: DeepSeek, a Chinese AI firm, has launched DeepSeek-V2.5, a powerful new open-supply language mannequin that combines common language processing and advanced coding capabilities. In K. Inui, J. Jiang, V. Ng, and X. Wan, editors, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 5883-5889, Hong Kong, China, Nov. 2019. Association for Computational Linguistics.

If you treasured this article and you would like to get more info relating to ديب سيك nicely visit our website.