NVIDIA/Megatron-LM
Ongoing research training transformer models at scale
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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.
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Latest capture 2026-07-15 03:16
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Scanned 2026-07-15 03:16
pyproject.toml
python ecosystem,
69 dependencies
uv.lock
python ecosystem,
0 dependencies
examples/cnn_qat/requirements.txt
python ecosystem,
1 dependency
examples/diffusers/requirements.txt
python ecosystem,
2 dependencies
examples/gpt-oss/requirements.txt
python ecosystem,
4 dependencies
examples/hf_ptq/requirements.txt
python ecosystem,
5 dependencies
examples/llm_distill/requirements.txt
python ecosystem,
3 dependencies
examples/llm_eval/requirements.txt
python ecosystem,
5 dependencies
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Ongoing research training transformer models at scale
Go ahead and axolotl questions
Minimalistic large language model 3D-parallelism training
🏗️ Fine-tune, build, and deploy open-source LLMs easily!
PyTorch native quantization and sparsity for training and inference
Efficent platform for inference and serving local LLMs including an OpenAI compatible API server.