DeepSeek Open-Sources Large-Scale Inference Framework DeepInfer Under Apache-2.0 License
DeepSeek has open-sourced its high-performance large-scale inference framework DeepInfer under the Apache-2.0 license. The framework supports optimized kernels, model and sampler runtime, parallelism strategies such as Attention DP and balanced CP, MoE EP plus EPLB, as well as DSpark and confidence-scheduled verification, SWA bounded replay, asynchronous scheduling with a zero-overhead batch scheduler, batch-invariant inference, deterministic sampling, and structured output. Ma Dongxi NLP reposted the news and said "Respect."
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The original text lists DeepInfer's features such as parallelism strategies and deterministic sampling, which can be used to assess its positioning in large-scale inference deployment.
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View original postDeepSeek just open sourced its high-performance, large-scale inference framework DeepInfer in Apache-2.0 license. https://t.co/W2cfi6O9LO Supported features: - Optimized kernels, model and sampler runtime - Parallelism: Attention DP / balanced CP, MoE EP + EPLB - DSpark and confidence-scheduled verification - SWA bounded replay - Asynchronous scheduling (zero-overhead batch scheduler) - Batch-invariant inference - Deterministic sampling - Structured output
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DeepSeek just open sourced its high-performance, large-scale inference framework DeepInfer in Apache-2.0 license. https://t.co/W2cfi6O9LO Supported features: - Optimized kernels, model and sampler runtime - Parallelism: Attention DP / balanced CP, MoE EP + EPLB - DSpark and confidence-scheduled verification - SWA bounded replay - Asynchronous scheduling (zero-overhead batch scheduler) - Batch-invariant inference - Deterministic sampling - Structured output
Body · AI translation
DeepSeek open-sources DeepInfer
Respect!