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InternLM Large Language Model

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Repository Introduction

[InternLM] (https://github.com/InternLM/InternLM) is the artificial intelligence Laboratory (Shanghai AI Laboratory) development of high-performance multimodal language model series. This product is based on the Huawei Cloud EulerOS 2.0 64-bit system of the arm architecture and provides the out-of-the-box InternLM2.5-1.8B-Chat model.

Key Features

  • Utilize trillions of high - quality corpora to build a super - strong knowledge system for the model.
  • Support a context window length of 8k, enabling longer inputs and a stronger inference experience.
  • Have general tool invocation capabilities, allowing users to flexibly build their own processes.
  • Provide a lightweight training framework for model pre - training. There's no need to install a large number of dependency packages. A single set of code supports pre - training on thousands of cards and single - card human preference alignment training, while achieving extreme performance optimization with an acceleration efficiency of nearly 90% under thousands of cards training.

The open - source image product InternLM Large Language Model provided by this project has InternLM2.5 - 1.8B - Chat and its related operating environment pre - installed, and also provides deployment templates. Come and refer to the usage guide to easily start your "out - of - the - box" efficient experience!

System requirements are as follows:

  • CPU: 4vCPUs or higher
  • RAM: 16GB or larger
  • Disk: At least 40GB

Prerequisites

Register a Huawei account and activate Huawei Cloud

Image Description

Image Specification Feature Description Remarks
internlm2_5-1_8b-chat-kunpeng Installed and deployed based on Kunpeng servers + Huawei Cloud EulerOS 2.0 64 - bit

Get Help

  • For more questions, you can contact us via issue or the service support of the specified product in the Huawei Cloud Marketplace.
  • For other open - source images, refer to open-source-image-repos

How to Contribute

  • Fork this repository and submit a merge request.
  • Synchronously update README.md based on your open - source image information.

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