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v0.1 consists of 7 large language models and 2 inference libraries to run rubra models. v0.0 is no longer supported as a majority of that work has moved to https://github.com/gptscript-ai/gptscript --------- Co-authored-by: Yingbei <yingbei@acorn.io>
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[submodule "tools.cpp"] | ||
path = tools.cpp | ||
url = https://github.com/rubra-ai/tools.cpp.git | ||
[submodule "vllm"] | ||
path = vllm | ||
url = https://github.com/rubra-ai/vllm.git | ||
[submodule "rubra-tools"] | ||
path = rubra-tools | ||
url = https://github.com/rubra-ai/rubra-tools.git |
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echo "Encountered dirty repo!"; \ | ||
git diff; \ | ||
exit 1 \ | ||
;fi | ||
;fi |
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<p align="left"> | ||
中文</a>  |  <a href="README.md">English</a> </a> | ||
</p> | ||
<br><br> | ||
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# Rubra | ||
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#### Rubra 是一系列开放权重、聚焦于工具调用的大模型(LLM)。 | ||
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Rubra 增强了当前最流行的一系列开放权重大模型(LLM)的工具调用能力。以能够在和用户对话时以稳定的方式调用用户定义的外部工具,使 Rubra 大模型非常适用于Agent相关的场景。 | ||
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所有模型均基于流行的Instruct模型,通过进一步的微调,有效地教授或增强模型调用工具的能力,同时尽可能减少模型在基础能力和知识上的流失。为了便于用户使用,我们扩展了流行的llm本地部署项目,让您可以轻松运行 Rubra 模型。 | ||
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## Rubra模型系列 | ||
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| 模型 | 最大上下文长度 | 大小 | 基础模型发布者 | | ||
|---------------------------------------------------------------|----------------|------|----------------------| | ||
| [rubra-ai/Meta-Llama-3-8B-Instruct](https://huggingface.co/rubra-ai/Meta-Llama-3-8B-Instruct) | 8,000 | 8B | Meta | | ||
| [rubra-ai/Meta-Llama-3-70B-Instruct](https://huggingface.co/rubra-ai/Meta-Llama-3-70B-Instruct) | 8,000 | 70B | Meta | | ||
| [rubra-ai/gemma-1.1-2b-it](https://huggingface.co/rubra-ai/gemma-1.1-2b-it) | 8,192 | 2B | Google | | ||
| [rubra-ai/Mistral-7B-Instruct-v0.3](https://huggingface.co/rubra-ai/Mistral-7B-Instruct-v0.3) | 32,000 | 7B | Mistral | | ||
| [rubra-ai/Mistral-7B-Instruct-v0.2](https://huggingface.co/rubra-ai/Mistral-7B-Instruct-v0.2) | 32,000 | 7B | Mistral | | ||
| [rubra-ai/Phi-3-vision-128k-instruct](https://huggingface.co/rubra-ai/Phi-3-vision-128k-instruct)| 128,000 | 3B | Microsoft | | ||
| [rubra-ai/Qwen2-7B-Instruct](https://huggingface.co/rubra-ai/Qwen2-7B-Instruct) | 131,072 | 7B | Qwen | | ||
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## Demo | ||
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在我们的 [Huggingface Spaces](https://huggingface.co/spaces/sanjay920/rubra-v0.1-dev) 上可以免费试用以上的大模型,不需要登录! | ||
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## 本地部署运行 Rubra 模型 | ||
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我们扩展了以下部署工具,以在 OpenAI 风格的API格式下本地运行 Rubra 模型: | ||
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- [llama.cpp](https://github.com/ggerganov/llama.cpp) | ||
- [vllm](https://github.com/vllm-project/vllm) | ||
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## 贡献 | ||
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欢迎您参与对 Rubra 的进一步开发!我们希望根据您的反馈改进模型的工具调用能力。如果您的工具调用不起作用或出错,请创建一个Issue并分享您遇到的问题。 | ||
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--- | ||
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## 许可证 | ||
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版权所有 (c) 2024 Acorn Labs, Inc. | ||
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根据 Apache License, Version 2.0(“许可证”)授权;您不得在不符合许可证的情况下使用此文件。您可以在以下网址获取许可证副本: | ||
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<http://www.apache.org/licenses/LICENSE-2.0> | ||
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除非适用法律要求或书面同意,按“原样”分发的软件不附带任何明示或暗示的保证或条件。请参阅许可证以了解特定语言的管理权限和限制。 |
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