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Releases: FederatedAI/FATE-Client

Release v2.2.0

31 Jul 11:29
f64eeb3
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Major improvements

  • Pipeline: support FATE-LLM 2.2.0, add FDKT support

Release v2.1.2

26 Jul 07:34
b666f5b
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Major improvements

  • Resolve the issue of missing certain dependency packages during standalone deployment without FATE installation.
  • Enable lightweight installation and usage without neural network-related algorithms.

Release v2.1.1

28 Jun 03:33
362c4e9
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Major improvements

  • Pipeline: add dump and load interface
  • Pipeline: Support FATE-LLM 2.1.0, add FedMKT support

Release v2.1.0

06 Mar 06:10
54dbeef
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Major improvements

  • Pipeline: add supports for fate-llm 2.0
    • newly added LLMModelLoader, LLMDatasetLoader, LLMDataFuncLoader
    • newly added configuration parsing of seq2seq_runner and ot_runner
  • Pipeline: unified input interface of components

Release v2.0.0

29 Dec 11:53
5383f59
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Feature Highlights

FATE-Client 2.0: Building Scalable Federated DSL for Application Layer Interconnection

  • Introduce new scalable and standardized federated DSL IR(Intermediate Representation) for federated modeling job
  • Compile python client to DSL IR
  • Federated DSL IR extension enhancement: supports multi-party asymmetric scheduling
  • Support mutual translation between Standardized Fate-2.0.0 DSL IR and BFIA protocol
  • Support using components with BFIA protocol through adapter mode
  • Migrated Flow CLI and Flow SDK

Release 2.0.0-beta

15 Sep 11:24
1af3d22
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Release 2.0.0-beta Pre-release
Pre-release

Major Features and Improvements

FATE-Client 2.0: Building Scalable Federated DSL for Application Layer Interconnection And Providing Tools For Fast Federated Modeling.

  • Migrated Flow CLI and Flow SDK
  • Updated federated DSL IR: enhance IR, add DataWarehouse and ModelWarehouse to load data and model from other sources
  • Update component definitions to support Fate-v2.0.0-beta
  • Flow CLI and PipeLine share configuration

Release v2.0.0-alpha

02 Feb 07:19
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Feature Highlights

Pipeline 2.0: Building Scalable Federated DSL for Application Layer Interconnection

  • Introduce new scalable and standardized federated DSL IR(Intermediate Representation) for federated modeling job
  • Compile python client to DSL IR
  • Support multiple scalable execution backends, including standalone and Fate-Flow.