Collection of best practices, reference architectures, model training examples and utilities to train large models on AWS.
-
Updated
Sep 11, 2025 - Shell
#
llm-training
Here are 5 public repositories matching this topic...
Run GPU inference and training jobs on serverless infrastructure that scales with you.
python data-science machine-learning deep-learning serverless hpc distributed-computing artificial-intelligence cloud-computing gpu-acceleration serverless-architectures gpu-computing cost-optimization ml-infrastructure mlops llm-serving llm-training
-
Updated
Jun 14, 2024 - Shell
Runpod-LLM provides ready-to-use container scripts for running large language models (LLMs) easily on RunPod.
llm runpod llms llmops llm-serving llamacpp llama-cpp llm-training llm-inference runpod-worker ollama llama-cpp-python ollama-api runpod-serverless runpods llamacpp-python runpod-endpoint
-
Updated
May 20, 2025 - Shell
NexusLLM is a GitHub repository dedicated to exploring various experiments related to Large Language Models (LLM). From fine-tuning and instruction-tuning to RAG and agent-based systems, it offers a diverse range of experiments and insights for researchers and enthusiasts interested in natural language processing and AI innovation.
-
Updated
Aug 15, 2025 - Shell
Containerized LLM for any use-case big or small
-
Updated
Sep 11, 2025 - Shell
Improve this page
Add a description, image, and links to the llm-training topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the llm-training topic, visit your repo's landing page and select "manage topics."