🚀 Improved Quantization Performance through Additional Training

This model has undergone additional training aimed at enhancing performance after quantization, and it is expected to achieve better performance than a model that has been directly quantized.

OpenBuddy - Open Multilingual Chatbot

GitHub and Usage Guide: https://github.com/OpenBuddy/OpenBuddy

Website and Demo: https://openbuddy.ai

Evaluation result of this model: Evaluation.txt

Copyright Notice

Built with Meta Llama 3

Base Model: nvidia/Llama-3.1-Nemotron-70B-Instruct

License: https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE

Acceptable Use Policy: https://llama.meta.com/llama3/use-policy

This model is intended for use in English and Chinese.

Prompt Format

We recommend using the fast tokenizer from transformers, which should be enabled by default in the transformers and vllm libraries. Other implementations including sentencepiece may not work as expected, especially for special tokens like <|role|>, <|says|> and <|end|>.

<|role|>system<|says|>You(assistant) are a helpful, respectful and honest INTP-T AI Assistant named Buddy. You are talking to a human(user).
Always answer as helpfully and logically as possible, while being safe. Your answers should not include any harmful, political, religious, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
You cannot access the internet, but you have vast knowledge, cutoff: 2023-04.
You are trained by OpenBuddy team, (https://openbuddy.ai, https://github.com/OpenBuddy/OpenBuddy), not related to GPT or OpenAI.<|end|>
<|role|>user<|says|>History input 1<|end|>
<|role|>assistant<|says|>History output 1<|end|>
<|role|>user<|says|>History input 2<|end|>
<|role|>assistant<|says|>History output 2<|end|>
<|role|>user<|says|>Current input<|end|>
<|role|>assistant<|says|>

This format is also defined in tokenizer_config.json, which means you can directly use vllm to deploy an OpenAI-like API service. For more information, please refer to the vllm documentation.

Disclaimer

All OpenBuddy models have inherent limitations and may potentially produce outputs that are erroneous, harmful, offensive, or otherwise undesirable. Users should not use these models in critical or high-stakes situations that may lead to personal injury, property damage, or significant losses. Examples of such scenarios include, but are not limited to, the medical field, controlling software and hardware systems that may cause harm, and making important financial or legal decisions.

OpenBuddy is provided "as-is" without any warranty of any kind, either express or implied, including, but not limited to, the implied warranties of merchantability, fitness for a particular purpose, and non-infringement. In no event shall the authors, contributors, or copyright holders be liable for any claim, damages, or other liabilities, whether in an action of contract, tort, or otherwise, arising from, out of, or in connection with the software or the use or other dealings in the software.

By using OpenBuddy, you agree to these terms and conditions, and acknowledge that you understand the potential risks associated with its use. You also agree to indemnify and hold harmless the authors, contributors, and copyright holders from any claims, damages, or liabilities arising from your use of OpenBuddy.

免责声明

所有OpenBuddy模型均存在固有的局限性，可能产生错误的、有害的、冒犯性的或其他不良的输出。用户在关键或高风险场景中应谨慎行事，不要使用这些模型，以免导致人身伤害、财产损失或重大损失。此类场景的例子包括但不限于医疗领域、可能导致伤害的软硬件系统的控制以及进行重要的财务或法律决策。