Releases: FederatedAI/FATE-Client
Releases · FederatedAI/FATE-Client
Release v2.2.0
Release v2.1.2
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
Major improvements
- Pipeline: add dump and load interface
- Pipeline: Support FATE-LLM 2.1.0, add FedMKT support
Release v2.1.0
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
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
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
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.