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--- |
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license: cc-by-sa-3.0 |
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datasets: |
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- mosaicml/dolly_hhrlhf |
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tags: |
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- Composer |
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- MosaicML |
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- llm-foundry |
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--- |
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# MPT-7B-Chat |
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MPT-7B-Chat is a chatbot-like model for dialogue generation. |
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It is built by finetuning [MPT-7B](https://huggingface.co/spaces/mosaicml/mpt-7b) on the [ShareGPT-Vicuna](https://huggingface.co/datasets/jeffwan/sharegpt_vicuna), [HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3), |
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[Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca), [HH-RLHF](https://huggingface.co/datasets/Anthropic/hh-rlhf), and [Evol-Instruct](https://huggingface.co/datasets/victor123/evol_instruct_70k) datasets. |
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* License: _CC-By-NC-SA-4.0_ (non-commercial use only) |
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* [Demo on Hugging Face Spaces](https://huggingface.co/spaces/mosaicml/mpt-7b-chat) |
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This model was trained by [MosaicML](https://www.mosaicml.com) and follows a modified decoder-only transformer architecture. |
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## Model Date |
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May 5, 2023 |
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## Model License |
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Apache-2.0 (commercial use permitted) |
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## Documentation |
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* [Blog post: Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs](www.mosaicml.com/blog/mpt-7b) |
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* [Codebase (mosaicml/llm-foundry repo)](https://github.com/mosaicml/llm-foundry/) |
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* Questions: Feel free to contact us via the [MosaicML Community Slack](https://join.slack.com/t/mosaicml-community/shared_invite/zt-w0tiddn9-WGTlRpfjcO9J5jyrMub1dg)! |
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### Example Dialogue |
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**SamIAm85**: |
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>I want you to come up with a tweet based on this summary of the article: |
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>"Introducing MPT-7B, the latest entry in our MosaicML Foundation Series. |
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>MPT-7B is a transformer trained from scratch on IT tokens of text and code. |
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>It is open source, available for commercial use, and it matches the quality of LLaMA-7B. |
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>MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. |
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>Starting today, you can train, finetune, and deploy your own private MPT models, either starting from one of our checkpoints or training from scratch. |
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>For inspiration, we are also releasing three finetuned models in addition to the base MPT-7B: MPT-7B-Instruct, MPT-7B-Chat, and MPT-7B-Story Writer-65k+, the last of which uses a context length of 65k tokens! |
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**MPT-7B-Instruct**: |
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>Here's my suggestion for a tweet: |
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>"Exciting news! @MosaicML has launched #MPT_7B - a new standard for open-source, commercially usable LLMs. With training on 17 tokens of text & code, it matches the quality of LLaMA-7B. Now you can train, fine-tune, and deploy your own private MPT models via their platform. Check out the full blog post here: https://bit.ly/3j6UJzZ" |
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**SamIAm85**: |
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>Is there anything you want to say to MosaicML about this exciting news? |
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**MPT-7B-Instruct**: |
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> As an Al language model myself, I am very impressed with the advancements made by MosaicML in developing such high-quality open-source LLMs. |
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> This new version of MPT-7B is truly impressive and I look forward to seeing what innovative applications developers will create using these powerful tools. |
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> Thank you for your hard work and dedication to advancing Al research and development. |
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## Acknowledgements |
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This model was finetuned by Sam Havens |
