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Releases: erfanzar/FJFormer

v0.0.75

12 Aug 19:30
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Release 0.0.75

What's New

1. Performance Optimization

  • Implemented advanced algorithms to enhance processing speed
  • Reduced memory footprint for more efficient resource utilization
  • Optimized critical paths to improve overall system responsiveness

2. Enhanced NF4 Data Type

  • Improved precision and accuracy of NF4 operations
  • Optimized NF4 conversions for better performance

3. Structural Enhancements

  • Refactored core components for improved modularity
  • Introduced a more intuitive project structure for easier navigation and maintenance
  • Updated dependency management for better compatibility and future-proofing

v0.0.70

17 Jul 23:24
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FJFormer 0.0.70 Release Notes

Major Improvements

Documentation

  • Comprehensive overhaul of documentation for better clarity and usability
  • Added more examples and use cases to help users get started quickly
  • Improved API references for easier navigation

LoRA (Low-Rank Adaptation)

  • Fixed critical issues affecting LoRA functionality
  • Introduced a new option to selectively save only A, B, and Alpha matrices in LoRA instead of the entire merged model
    • This feature significantly reduces storage requirements and improves flexibility in model management

Checkpoint Managers

  • Updated with enhanced functionality for more efficient model state handling
  • Improved integration with distributed training workflows

Removed Features

  • The FJFormer Linen API has been deprecated and removed from this version

New Features

ImplicitArray

  • Using core.ImplicitArray, a powerful abstraction for handling large arrays without instantiation
  • Enables lazy evaluation and efficient array operations in JAX

Quantization Support

  • Added Array8Bit for 8-bit quantization
    • Reduces model size while maintaining good performance
  • Introduced Array4Bit for 4-bit quantization (NF4)
    • Offers extreme model compression for scenarios where size is critical

0.0.40

28 Mar 13:26
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Summery

  1. Fixing Splash Attention Kernel
  2. Improving project structure
  3. adding new loss function useable and related to MoE Models

What's Changed

  • Add compute_weighted_cross_entropy_and_accuracy() by @yhavinga in #1
  • Fix Cosine with Warmup Scheduler by @w11wo in #2

New Contributors

Full Changelog: v0.0.22...v0.0.40

v0.0.22

09 Jan 10:15
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Full Changelog: v0.0.16...v0.0.22

v0.0.16

29 Nov 11:25
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