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@deepjavalibrary

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Deep Java Library

Joined March 2020
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@krshubham1708
Kumar Shubham
2 years
Here's a link to the full video:
@krshubham1708
Kumar Shubham
2 years
Hey @deepjavalibrary community, here's a trailer to my video (in the replies) on how to get started with building a semantic text similarity engine using a pretrained huggingface model.
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@deepjavalibrary
djl
2 years
Learn how to build your own AI powered video surveillance system in just 150 lines of code https://t.co/MJB5jhzRFr
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@deepjavalibrary
djl
2 years
DJL v0.23.0 was released. It adds support for XGBoost and FastText on aarch64, streaming, and LLM text generation. Serving features rolling batches, lmi-dist, PEFT and LoRA handler support, and an s3 cache engine. See the full release notes at
Tweet card summary image
github.com
Key Features Upgrades for engines Upgrades PyTorch engine to 2.0.1 Upgrades javacpp version to 1.5.9 (#2636) Upgrades HuggingFace tokenizer to 0.13.3 (#2697) Upgrades OnnxRuntime version to 1.15...
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@petebankhead
Pete Bankhead
3 years
v0.4.0 brings QuPath a lot closer to supporting deep learning routinely, with the help of @deepjavalibrary It's still early - the focus has been on the unglamorous make-it-possible stuff - but I think it can already be pretty useful. https://t.co/yemfFmVbK7
@petebankhead
Pete Bankhead
3 years
Close.
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@paulk_asert
Paul King
3 years
Natural Language Processing with Groovy, OpenNLP, CoreNLP, Nlp4j, Datumbox, Smile, Spark NLP, DJL and TensorFlow https://t.co/mMEmQoOEbh #groovylang @ApacheSpark @ApacheGroovy @deepjavalibrary @TensorFlow @ApacheOpennlp @stanfordnlp @haifengl @Datumbox @oyahiroki
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@deepjavalibrary
djl
3 years
DJL v0.17.0 is now out and features support for @PyTorch linux AArch64 and version v1.11.0, @onnxruntime v1.11.0, two new datasets, and more. Find it now on #MavenCentral and the GitHub release at https://t.co/AaUzVlXE9I
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@deepjavalibrary
djl
4 years
To learn how to deploy your @huggingface #nlp #deeplearning model in #Java, check out the latest #djl blog post https://t.co/QJ5X0He08b
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@deepjavalibrary
djl
4 years
Read the post on @OpenAtMicrosoft about how @hypefactors was able to scale up their @PyTorch named entity recognition (NER) transformer model to billions of daily inferences using @onnxruntime and #djl: https://t.co/N159KWxQ3u
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@deepjavalibrary
djl
4 years
Learn how @hypefactors was able to simplify their #ml #MLOps using @onnxai and #djl: https://t.co/WgQTHoVEiW
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@deepjavalibrary
djl
4 years
DJL 0.16.0 is now out and features support for @ApacheMXNet 1.9.0 with #CUDA 11.2, improved @onnxruntime memory configuration, and a cleaner integration with #FastText. Find it now on #MavenCentral and the GitHub release at https://t.co/LAXwhkDs4J.
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@deepjavalibrary
djl
4 years
You can speed up your #Java #Scala #DeepLearning by combining #djl, GPUs on @ApacheSpark 3.0, @NVIDIAAI RAPIDS, and run it on #aws #elasticmapreduce. Read https://t.co/JOA2SRfjIq to learn more
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@deepjavalibrary
djl
4 years
Aprendizaje profundo con Spark en la biblioteca Deep Java en 10 minutos:
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