DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model DeepSeek-AI research@deepseek.com Abstract We present DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized utilization of LLMs. In order to tackle this problem, we introduce DeepSeek-V2, a strong open-source Mixture-of-Experts (MoE) language model, characterized by economical training and efficient inference through Huang, F. Luo, C. Ruan, Z. Sui, and W. Liang. Deepseekmoe: Towards ultimate expert specialization in mixture-of-experts language models. CoRR, abs/2401.06066, 2024. URL https://doi.org/10.48550/arXiv.2401.06066

“helv”, “tiro” etc., and you will get away with about 35 KB compressed. If you know you have a mixture of CJK and Latin text, consider just using Font("cjk") because this supports everything and also width. Lines not fitting into the box will be invisible. • text (str) – the text. May contain any mixture of Latin, Greek, Cyrillic, Chinese, Japanese and Korean characters. The respective required font (Changed in v1.14.20) A list or tuple must consist of rect_like or quad_like items (or even a mixture of either). Every item must be finite, convex and not empty (as applicable). Set this parameter to

We will study forward proofs more deeply in Chapter 3. Informal proofs are sometimes written in a mixture of both styles. This is man- ageable as long as the backward steps are clearly identified, by such plished,” meaning that no subgoals remain to be proved. The proof is a typical intro–apply–ex act mixture. It uses the lemmas and.intro : ?a → ?b → ?a ∧ ?b and.elim_left : ?a ∧ ?b → ?a and.elim_right resort to tactical proofs for proving subgoals or uninteresting intermediate steps. Another kind of mixture arises when we pass arguments to lemma names. For example, given hab : a → b and ha : a, the tactic

com/generative-models/ Our Goal: ?(?) https://www.mathworks.com/help/stats/simulate-data-from-a-gaussian-mixture- model.html What does ? ? looks like? http://www.pymvpa.org/examples/mdp_mnist.html emm, how to

and machine learning. ● PyMC is for your Bayesian/MCMC/hierarchical modeling needs. ● PyMix for mixture models ● If speed becomes a problem, consider Theano. Theano is a Python library that allows you

recognition of the diverse range of hardware in the field—a project might run in AWS, Azure or GCP (or a mixture), and so the SmartEdge infrastructure had to support multiple architectures in a variety of flavors

repository but lacks the automation benefits of pull-based deployments. Complex architectures with a mixture of Kubernetes and non-Kubernetes workloads can leverage a combination of both. Robust observability

only is the clusters are roughly of equal sizes Probabilistic clustering methods such as Gaussian mixture models can handle both these issues (model each cluster using a Gaussian distri- bution) K-means

to implement alias pointers Possible avenues for further work • Hybrid algorithm? Can we do a mixture of split reference count and deferred reclamation to get performance that is always competitive

application. TPC‐C simulates a wholesale supplier and is centered on processing orders. It is a mixture of read‐only and update‐intensive transactions that represent complex OLTP application activities