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examples/end-to-end-examples/support_chatbot/README.md

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 In this tutorial, we will be creating an application that answers questions about the MosaicML composer codebase. The basic structure of this application will be a retrieval question answering system where the user will provide the chatbot with a question, and then a language model will answer the question based on the retrieved text. See some [great](https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html#retrieval-question-answering) [materials](https://blog.langchain.dev/langchain-chat/) from [LangChain](https://python.langchain.com/en/latest/index.html) for more exploration on this type of application.
 
-By default the model that is used throughout is [MPT-7b](https://huggingface.co/mosaicml/mpt-7b), a 7-billion parameter large language model trained by MosaicML. See [our blog](https://www.mosaicml.com/blog/mpt-7b) for more details. We have also released a more powerful, 30-billion parameter model, which you can swap in to this example very easily. See [MPT-30b](https://huggingface.co/mosaicml/mpt-30b) for more details. To swap in the 30b model, all you need to do is change all occurrences of `mpt-7b` to `mpt-30b`. The important ones to change are the `model.pretrained_model_name_or_path` and the `tokenizer.name`, in the various [finetune](./mcli-yamls/finetune/) yamls. The other occurrences are just in names of runs and save folders. Depending on your hardware, and particularly if you get a CUDA `c10` error, you may also need to change `device_train_microbatch_size` from `auto` to `1` in the [finetune](./mcli-yamls/finetune/) yamls.
+By default the model that is used throughout is [MPT-30b](https://huggingface.co/mosaicml/mpt-30b), a 30-billion parameter large language model trained by MosaicML. See [our blog](https://www.mosaicml.com/blog/mpt-30b) for more details. Depending on your hardware, and particularly if you get a CUDA `c10` error, you may also need to change `device_train_microbatch_size` from `auto` to `1` in the [finetune](./mcli-yamls/finetune/) yamls.
 
 ![demo](web_app_screenshot.png)