Best practice for training LLaMA models in Megatron-LM
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Updated
Jan 2, 2024 - Python
Best practice for training LLaMA models in Megatron-LM
Annotations of the interesting ML papers I read
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
Large scale 4D parallelism pre-training for 🤗 transformers in Mixture of Experts *(still work in progress)*
Odysseus: Playground of LLM Sequence Parallelism
A LLaMA1/LLaMA12 Megatron implement.
Training NVIDIA NeMo Megatron Large Language Model (LLM) using NeMo Framework on Google Kubernetes Engine
Megatron-LM/GPT-NeoX compatible Text Encoder with 🤗Transformers AutoTokenizer.
Minimal yet high performant code for pretraining llms. Attempts to implement some SOTA features. Implements training through: Deepspeed, Megatron-LM, and FSDP. WIP
Running Large Language Model easily.
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