Repository profile
PyTorch native quantization and sparsity for training and inference
Repository updates
Get generated pytorch/ao 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 2026-07-17 04:06
48 captures since 2026-05-25
Stars from baseline +69
All tracked data
Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.
Scanned 2026-07-17 04:06
pyproject.toml
python ecosystem,
2 dependencies
setup.py
python ecosystem,
0 dependencies
docs/requirements.txt
python ecosystem,
12 dependencies
examples/sam2_amg_server/requirements.txt
python ecosystem,
13 dependencies
examples/sam2_vos_example/requirements.txt
python ecosystem,
2 dependencies
torchao/experimental/CMakeLists.txt
c-cpp ecosystem,
1 dependency
torchao/csrc/cpu/CMakeLists.txt
c-cpp ecosystem,
2 dependencies
torchao/prototype/autoround/requirements.txt
python ecosystem,
4 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.
AI agent config detected
Key config paths
Nearest indexed repositories by embedding similarity.
Accessible large language models via k-bit quantization for PyTorch.
Go ahead and axolotl questions
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.
QLoRA: Efficient Finetuning of Quantized LLMs
PyTorch native post-training library
A PyTorch native platform for training generative AI models
