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Updating RAFT paper and minor fixes to RAFT blog (#263)
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ShishirPatil authored Mar 15, 2024
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<a class="author" href="https://tianjunz.github.io">Tianjun Zhang</a>
<a class="author" href="https://shishirpatil.github.io/">Shishir G. Patil</a>
<a class="author" href="https://www.linkedin.com/in/kaiwen129/">Kai Wen</a>
<a class="author" href="https://naman-ntc.github.io/">Naman Jain</a>
<a class="author" href="https://sincerass.github.io/">Sheng Shen</a>
<a class="author" href="https://people.eecs.berkeley.edu/~matei/">Matei Zaharia</a>
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<a class="author" href="https://www.linkedin.com/in/kaiwen129/"> Core Contributor: Kai Wen</a>
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The RAFT model is trained on top of the base model Llama2-7B from Meta and on Microsoft AI Studio. We provide a short tutorial on how to train your own RAFT model for RAG applications.
For more details about RAFT please refer to our <a href="https://github.com/ShishirPatil/gorilla/blob/gh-pages/assets/RAFT.pdf ">paper</a> and <a href="aka.ms">Microsoft-Meta blog</a>.
For more details about RAFT please refer to our <a href="https://github.com/ShishirPatil/gorilla/blob/gh-pages/assets/RAFT.pdf ">paper</a> and <a href="aka.ms/raft-blog">Microsoft-Meta blog</a>.
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