@@ -268,12 +268,12 @@ If you're interested in the field of LLM, you may find the above list of milesto
-[Megatron-DeepSpeed](https://github.com/microsoft/Megatron-DeepSpeed) - DeepSpeed version of NVIDIA's Megatron-LM that adds additional support for several features such as MoE model training, Curriculum Learning, 3D Parallelism, and others.
-[torchtune](https://github.com/pytorch/torchtune) - A Native-PyTorch Library for LLM Fine-tuning.
-[torchtitan](https://github.com/pytorch/torchtitan) - A native PyTorch Library for large model training.
-[NeMo Framework](https://github.com/NVIDIA/NeMo) - Generative AI framework built for researchers and PyTorch developers working on Large Language Models (LLMs), Multimodal Models (MMs), Automatic Speech Recognition (ASR), Text to Speech (TTS), and Computer Vision (CV) domains.
-[Megatron-LM](https://github.com/NVIDIA/Megatron-LM) - Ongoing research training transformer models at scale.
-[Colossal-AI](https://github.com/hpcaitech/ColossalAI) - Making large AI models cheaper, faster, and more accessible.
-[BMTrain](https://github.com/OpenBMB/BMTrain) - Efficient Training for Big Models.
-[Mesh Tensorflow](https://github.com/tensorflow/mesh) - Mesh TensorFlow: Model Parallelism Made Easier.
-[maxtext](https://github.com/google/maxtext) - A simple, performant and scalable Jax LLM!
-[Alpa](https://alpa.ai/index.html) - Alpa is a system for training and serving large-scale neural networks.
-[maxtext](https://github.com/AI-Hypercomputer/maxtext) - A simple, performant and scalable Jax LLM!
-[GPT-NeoX](https://github.com/EleutherAI/gpt-neox) - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
