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1 repositorio

Awesome GitHub RepositoriesModel Layer Patching

Runtime replacement of specific neural network layers with optimized implementations without source code changes.

Distinct from Runtime Method Patching: Distinct from Runtime Method Patching: targets ML model layers specifically, not general application methods.

Explore 1 awesome GitHub repository matching testing & quality assurance · Model Layer Patching. Refine with filters or upvote what's useful.

Awesome Model Layer Patching GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • linkedin/liger-kernelAvatar de linkedin

    linkedin/Liger-Kernel

    6,148Ver en GitHub↗

    Liger-Kernel is a collection of pre-built fused Triton kernels and patching utilities designed to accelerate large language model training. It provides drop-in kernel replacements for common LLM operations such as RMSNorm, cross-entropy loss, and attention, enabling increased throughput and reduced memory usage while preserving bitwise-exact gradients. The project serves as a toolkit for composing custom model architectures from individual optimized kernels and for patching pre-existing models with minimal code changes. The project distinguishes itself through its ability to perform runtime m

    Enables runtime monkey-patching of Hugging Face and Megatron-LM model layers with optimized Triton kernels.

    Pythonfinetuninggemma2hacktoberfest
    Ver en GitHub↗6,148
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  2. Testing & Quality Assurance
  3. Function Call Tracking
  4. Function Behavior Replacement
  5. Runtime Method Patching
  6. Model Layer Patching