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Add 8k transformers link (#14) 

* add links for 8k
* fix acknowledgement
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yhcc 2023-07-06 22:00:50 +08:00 committed by GitHub
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@ -67,6 +67,8 @@ InternLM ，即书生·浦语大模型，包含面向实用场景的70亿参数
| -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ |
| **InternLM 7B** | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b) | [🤗internlm/intern-7b](https://huggingface.co/internlm/internlm-7b) |
| **InternLM Chat 7B** | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](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** | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-8k) | [🤗internlm/intern-chat-7b-8k](https://huggingface.co/internlm/internlm-chat-7b-8k)
**局限性：** 尽管在训练过程中我们非常注重模型的安全性，尽力促使模型输出符合伦理和法律要求的文本，但受限于模型大小以及概率生成范式，模型可能会产生各种不符合预期的输出，例如回复内容包含偏见、歧视等有害内容，请勿传播这些内容。由于传播不良信息导致的任何后果，本项目不承担责任。
@ -163,7 +165,7 @@ TKS 代表平均每GPU每秒可以处理的 Token 数量。更多的性能测试
## 致谢
InternLM 代码库是一款由上海人工智能实验室和来自不同高校、企业的研发人员共同参与贡献的开源项目。我们感谢所有为项目提供新功能支持的贡献者，以及提供宝贵反馈的用户。 我们希望这个工具箱和基准测试可以为社区提供灵活高效的代码工具，供用户微调 InternLM 并开发自己的新模型，从而不断为开源社区提供贡献。特别鸣谢flash-attention (https://github.com/HazyResearch/flash-attention) 与 ColossalAI (https://github.com/hpcaitech/ColossalAI) 两项开源项目。
InternLM 代码库是一款由上海人工智能实验室和来自不同高校、企业的研发人员共同参与贡献的开源项目。我们感谢所有为项目提供新功能支持的贡献者，以及提供宝贵反馈的用户。 我们希望这个工具箱和基准测试可以为社区提供灵活高效的代码工具，供用户微调 InternLM 并开发自己的新模型，从而不断为开源社区提供贡献。特别鸣谢[flash-attention](https://github.com/HazyResearch/flash-attention) 与 [ColossalAI](https://github.com/hpcaitech/ColossalAI) 两项开源项目。
## 开源许可证

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README.md
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@ -69,6 +69,7 @@ InternLM 7B and InternLM 7B Chat, trained using InternLM, have been open-sourced
| -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ |
| **InternLM 7B** | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-7b) | [🤗internlm/intern-7b](https://huggingface.co/internlm/internlm-7b) |
| **InternLM Chat 7B** | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](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** | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/InternLM-chat-7b-8k) | [🤗internlm/intern-chat-7b-8k](https://huggingface.co/internlm/internlm-chat-7b-8k)
**Limitations:** Although we have made efforts to ensure the safety of the model during the training process and to encourage the model to generate text that complies with ethical and legal requirements, the model may still produce unexpected outputs due to its size and probabilistic generation paradigm. For example, the generated responses may contain biases, discrimination, or other harmful content. Please do not propagate such content. We are not responsible for any consequences resulting from the dissemination of harmful information.
@ -170,7 +171,7 @@ We appreciate all the contributors for their efforts to improve and enhance Inte
## Acknowledgements
InternLM codebase is an open-source project contributed by Shanghai AI Laboratory and researchers from different universities and companies. We would like to thank all the contributors for their support in adding new features to the project and the users for providing valuable feedback. We hope that this toolkit and benchmark can provide the community with flexible and efficient code tools for fine-tuning InternLM and developing their own models, thus continuously contributing to the open-source community. Special thanks to the two open-source projects, flash-attention (https://github.com/HazyResearch/flash-attention) and ColossalAI (https://github.com/hpcaitech/ColossalAI).
InternLM codebase is an open-source project contributed by Shanghai AI Laboratory and researchers from different universities and companies. We would like to thank all the contributors for their support in adding new features to the project and the users for providing valuable feedback. We hope that this toolkit and benchmark can provide the community with flexible and efficient code tools for fine-tuning InternLM and developing their own models, thus continuously contributing to the open-source community. Special thanks to the two open-source projects, [flash-attention](https://github.com/HazyResearch/flash-attention) and [ColossalAI](https://github.com/hpcaitech/ColossalAI).
## Open Source License