Download Latest Version
Release v2.2.0 source code.tar.gz (43.4 MB)
Get an email when there's a new version of FATE
| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| README.md | 2024-03-06 | 2.1 kB | |
| Release v2.1.0 source code.tar.gz | 2024-03-06 | 43.0 MB | |
| Release v2.1.0 source code.zip | 2024-03-06 | 44.0 MB | |
| Totals: 3 Items | 87.0 MB | 0 | |
By downloading, installing or using the software, you accept and agree to be bound by all of the terms and conditions of the LICENSE and DISCLAIMER.
Major Features and Improvements
Arch * Some bugs fixed for spark computing engine
Component * Unified IO keys naming format for all components * Add LLMLoader to support running FATE-LLM v2.0 with pipeline
OSX * Compatible with eggroll-v2.x
EggRoll * add 2.x api backport support * bug fix
Major Features and Improvements
- Improved the display issue of output data.
- Enhanced the PyPI package: configuration files have been relocated to the user's home directory, and the relative paths for uploading data are based on the user's home directory.
- Added support for running FATE algorithms with Spark + Hadoop.
Bug-Fix
- Fixed an issue where failed tasks could not be retried.
- Fixed an issue where the system couldn't run when the task cores exceeded the system total cores.
FATE-Client * 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
FATE-LLM * Adapt to fate-v2.0 framework: * Migrate parameter-efficient fine-tuning training methods and models. * Migrate Standard Offsite-Tuning and Extended Offsite-Tuning（Federated Offsite-Tuning+) * Newly trainer，dataset, data_processing function design * New FedKSeed Federated Tuning Algorithm: train large language models in a federated learning setting with extremely low communication cost
FATE-Test * Add Support for Job Runtime Configuration