Performance- DJL serving running multithreading inference in a single JVM. Our benchmark shows DJL serving has higher throughput than most C++ model servers on the market Ease of use- DJL serving can serve most models out of the box Easy to extend- DJL serving plugins make it easy to add ...
import com.github.gradle.node.npm.task.NpmTask plugins { ai.djl.javaProject id("com.github.node-gradle.node") version "3.4.0" } dependencies { api(project(":serving")) } tasks { register<NpmTask>("buildConsoleApp") { dependsOn("npmInstall") project.logger.info("Build the DJL Manageme...
DJL Serving 是一種高效能通用獨立模型服務解決方案。它需要深度學習模型、數個模型或工作流程,並透過 HTTP 端點提供這些模型。 您可以使用其中一個 DJL ServingDeep Learning Containers (DLCs)來為您的 AWS模型提供服務。若要瞭解支援的模型類型與架構,請參閱DJL Serving GitHub 儲存庫。
v0.29.0 c343d60 Key Features Details regarding the latest LMI container image_uris can be foundhere DJL Serving Changes (applicable to all containers) Allows configuring health checks to fail based on various types of error rates When not streaming responses, all invocation errors will respond wit...
A universal scalable machine learning model deployment solution - djl-serving/serving/docs/configurations_model.md at master · deepjavalibrary/djl-serving
djl-serving: update 0.29.0 bottle. 1c5f66f github-actions bot added the CI-published-bottle-commits label Jul 19, 2024 github-actions bot approved these changes Jul 19, 2024 View reviewed changes BrewTestBot enabled auto-merge July 19, 2024 11:39 BrewTestBot added this pull request...
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serving/docker/lmi.DockerfileOutdated @@ -37,7 +37,7 @@ ARG flash_attn_2_wheel="https://github.com/vllm-project/flash-attention/releases ARGflash_infer_wheel="https://github.com/flashinfer-ai/flashinfer/releases/download/v0.1.6/flashinfer-0.1.6+cu124torch2.4-cp310-cp310-linux_x86_64...
You can refer to our [Multithreading Benchmark](https://github.com/deepjavalibrary/djl/blob/master/extensions/benchmark/src/main/java/ai/djl/benchmark/MultithreadedBenchmark.java) as an example, You can refer to our [Multithreading Benchmark](https://github.com/deepjavalibrary/djl-serving/blob...
Performance- DJL serving running multithreading inference in a single JVM. Our benchmark shows DJL serving has higher throughput than most C++ model servers on the market Ease of use- DJL serving can serve most models out of the box Easy to extend- DJL serving plugins make it easy to add ...