Repository profile
A Flexible Framework for Experiencing Heterogeneous LLM Inference/Fine-tune Optimizations
Repository updates
Get generated kvcache-ai/ktransformers development summaries by email, or follow the weekly and monthly RSS feeds.
Sign in to subscribe by email. RSS feeds are public.
Sign in to subscribeTracked growth, recent movement, and commit velocity from stored repository snapshots.
Latest capture 2026-07-15 03:14
5 captures since 2026-05-25
Stars from baseline +239
All tracked data
Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.
Scanned 2026-07-15 03:14
pyproject.toml
python ecosystem,
1 dependency
setup.py
python ecosystem,
2 dependencies
archive/pyproject.toml
python ecosystem,
17 dependencies
archive/setup.py
python ecosystem,
0 dependencies
kt-kernel/CMakeLists.txt
c-cpp ecosystem,
4 dependencies
kt-kernel/pyproject.toml
python ecosystem,
18 dependencies
kt-kernel/requirements.txt
python ecosystem,
5 dependencies
kt-kernel/setup.py
python ecosystem,
0 dependencies
Searchable topics, generated tags, and stack labels that explain where this repository fits.
Agent instructions and tool configuration paths found in the repository tree.
Nearest indexed repositories by embedding similarity.
Ongoing research training transformer models at scale
Fast inference engine for Transformer models
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
A Next-Generation Training Engine Built for Ultra-Large MoE Models
Efficient Triton Kernels for LLM Training
llama.cpp fork with additional SOTA quants and improved performance
