OpenMMLab·Jan 16, 2025InternLM3 Open Source: Achieving High-Performance Models with 4T DataWritten by InternLM Team
OpenMMLab·Sep 1, 2023Announcing XTuner: An Efficient Finetune Toolkit for LLMWith XTuner, 8GB GPU memory is all you need to create your own AI assistant.A response icon1A response icon1
OpenMMLab·Aug 24, 2023The AI New Era: How Should Large Models “Rack Their Brains”How do we address the shortcomings of large language models in complex reasoning? By using the chain-of-thought prompting technique!
OpenMMLab·Aug 18, 2023Benchmarking the multi-modal capability of Bard with MMBenchIn order to provide an overview of Bard’s multi-modal ability, we evaluate it on the test split of MMBench as below and compare it with…
OpenMMLab·Aug 16, 2023Faster and More Efficient 4-bit quantized LLM Model InferenceLMDeploy has released an exciting new feature — 4-bit quantization and inference. This not only trims down the model’s memory overhead to…A response icon1A response icon1
OpenMMLab·Aug 10, 2023Thoroughly evaluate AX620A from the perspective of security industryFrom the perspective of security business, we have conducted a comprehensive test of AX620A, covering various evaluation indicators such as
OpenMMLab·Aug 2, 2023Deploy Llama-2 models easily with LMDeploy!This article will guide you on how to quickly deploy the Llama-2 models with LMDeploy.
OpenMMLab·Aug 1, 2023It’s 2023. Is PyTorch’s FSDP the best choice for training large models?Why codebase for training large models tends to use frameworks like DeepSpeed or ColossalAI ，with scant regard for PyTorch’s native FSDP…A response icon2A response icon2
OpenMMLab·Jul 27, 2023Fine-tuning Llama2 takes less than 200 lines of code!This article will guide you on how to fine-tuning Llama2 takes less than 200 lines of code!
OpenMMLab·Jul 24, 2023Join OpenMMLab Codecamp: Harness Your Coding Skills and Shape the Future of Open Source!Want to improve programming skills?
