DeepSeek-V2: A faster, cheaper language model that reads really long texts
DeepSeek-V2 is a big language model that makes it cheaper and quicker to train and run, while still being very capable.
it comprise 236B parameters but only about 21B are used per token, so it uses less work for each sentence.
It can handle very long inputs, up to 128K tokens, which means it can read long documents, books, or long chats without losing track.
The design uses smart tricks to shrink the memory the model needs and to run only parts of the model at a time, so training cost drops a lot and speed goes up.
For example, it roughly saves 42.
5% of training cost and runs up to 5.
76x faster on some tasks.
The model was trained on a huge mix of clean text and then tuned to chat better.
You might see more helpful answers, longer context memory, and quicker replies.
Not perfect, but it's a big step toward powerful models that don't demand huge time or money to use.
Read article comprehensive review in Paperium.net:
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts LanguageModel
🤖 This analysis and review was primarily generated and structured by an AI . The content is provided for informational and quick-review purposes.
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