From 58108413bde753f56363815e2327311ff9db9d3b Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Tue, 22 Aug 2023 07:46:01 +0800 Subject: [PATCH] Update readme for news of InternLM-Chat-7B-v1.1 and Lagent (#213) * update readme * fix typo --- README-zh-Hans.md | 5 +++++ README.md | 11 +++++++---- 2 files changed, 12 insertions(+), 4 deletions(-) diff --git a/README-zh-Hans.md b/README-zh-Hans.md index ad19550..e7c0a45 100644 --- a/README-zh-Hans.md +++ b/README-zh-Hans.md @@ -45,6 +45,10 @@ InternLM ,即书生·浦语大模型,包含面向实用场景的70亿参数 提供了支持模型预训练的轻量级训练框架,无需安装大量依赖包,一套代码支持千卡预训练和单卡人类偏好对齐训练,同时实现了极致的性能优化,实现千卡训练下近90%加速效率。 +## 新闻 + +我们开源了 InternLM-Chat-7B v1.1。该模型能够调用代码解释器和工具插件。你可以在 [Lagent](https://github.com/InternLM/lagent) 中体验这些新功能。 + ## InternLM-7B ### 性能评测 @@ -74,6 +78,7 @@ InternLM ,即书生·浦语大模型,包含面向实用场景的70亿参数 | 模型 | InternLM 格式权重下载地址 | Transformers 格式权重下载地址 | | -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ | | **InternLM 7B** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b) | [🤗internlm/intern-7b](https://huggingface.co/internlm/internlm-7b) | +| **InternLM Chat 7B v1.1** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-v1.1) | [🤗internlm/intern-chat-7b-v1.1](https://huggingface.co/internlm/internlm-chat-7b-v1.1) | | **InternLM Chat 7B** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b) | [🤗internlm/intern-chat-7b](https://huggingface.co/internlm/internlm-chat-7b) | **InternLM Chat 7B 8k** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-8k) | [🤗internlm/intern-chat-7b-8k](https://huggingface.co/internlm/internlm-chat-7b-8k) diff --git a/README.md b/README.md index 090e762..b7cd781 100644 --- a/README.md +++ b/README.md @@ -35,9 +35,6 @@ 👋 join us on <a href="https://twitter.com/intern_lm" target="_blank">Twitter</a>, <a href="https://discord.gg/xa29JuW87d" target="_blank">Discord</a> and <a href="https://r.vansin.top/?r=internwx" target="_blank">WeChat</a> </p> - - - ## Introduction InternLM has open-sourced a 7 billion parameter base model and a chat model tailored for practical scenarios. The model has the following characteristics: @@ -48,6 +45,11 @@ InternLM has open-sourced a 7 billion parameter base model and a chat model tail Additionally, a lightweight training framework is offered to support model pre-training without the need for extensive dependencies. With a single codebase, it supports pre-training on large-scale clusters with thousands of GPUs, and fine-tuning on a single GPU while achieving remarkable performance optimizations. InternLM achieves nearly 90% acceleration efficiency during training on 1024 GPUs. +## News + +InternLM-7B-Chat v1.1 is released with code interpreter and function calling capability. You can try it with [Lagent](https://github.com/InternLM/lagent) +- + ## InternLM-7B ### Performance Evaluation @@ -77,6 +79,7 @@ InternLM 7B and InternLM 7B Chat, trained using InternLM, have been open-sourced | Model | InternLM Format Weight Download Link | Transformers Format Weight Download Link | | ----------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------- | | **InternLM 7B** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b) | [🤗internlm/intern-7b](https://huggingface.co/internlm/internlm-7b) | +| **InternLM Chat 7B v1.1** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-v1.1) | [🤗internlm/intern-chat-7b-v1.1](https://huggingface.co/internlm/internlm-chat-7b-v1.1) | | **InternLM Chat 7B** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b) | [🤗internlm/intern-chat-7b](https://huggingface.co/internlm/internlm-chat-7b) | | **InternLM Chat 7B 8k** | [](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-8k) | [🤗internlm/intern-chat-7b-8k](https://huggingface.co/internlm/internlm-chat-7b-8k) | @@ -136,7 +139,7 @@ We use [LMDeploy](https://github.com/InternLM/LMDeploy) to complete the one-clic ``` 3. After exporting the model, you can start a server and have a conversation with the deployed model using the following command: - + ```bash bash workspace/service_docker_up.sh python3 -m lmdeploy.serve.client {server_ip_addresss}:33337