davanstrien HF staff commited on
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99c3ad0
1 Parent(s): bbe1860

Update login.html to fix heading tag and update hyperlinks

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  1. login.html +9 -9
login.html CHANGED
@@ -40,24 +40,24 @@
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  <div class="left-align">
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  <h2>What's covered?</h2>
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  <p>Currently this Space has notebooks covering the following topics:</p>
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- <h4>Creating synthetic text similarity datasets:</h4>
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  <p>
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- A series of notebooks covering the steps for creating a synthetic dataset for
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  fine-tuning a sentence similarity model. These notebooks cover:
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  </p>
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  <ul>
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  <li>
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  How to do structured generation using the
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- <a href="https://github.com/outlines-dev/outlines">outlines</a> library
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  to have more control on the outputs generated by a LLM.
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  </li>
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  <li>
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  How to use
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- <a href="https://docs.llamaindex.ai/en/stable/">Llama-index</a> to chunk
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  texts to fit into the context length of sentence embedding models.
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- </li>
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- <li>
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- Using <a href="https://github.com/vllm-project/vllm">vLLM</a> to
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  efficiently create a dataset that can be used to fine-tune a Sentence
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  similarity model.
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  </li>
@@ -66,11 +66,11 @@
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  <div class="center-align">
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  <h2>Using the Space</h2>
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  <p>
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- To use this Space, you should <a href="https://huggingface.co/spaces/davanstrien/synthetic-data-workshop?duplicate=true">duplicate it</a>.
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  To ensure your work is saved it's suggested to enable persistent storage for your Space.
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  To start, you may want to use a smaller GPU like the T4 and switch out to a bigger GPU when you want to run larger LLMs or generate more data.
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  <b>Reminder</b> you can preview the notebooks in the Space without running
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- them. You can find the Jupyter Notebooks in the <a href="https://huggingface.co/spaces/davanstrien/synthetic-data-workshop/tree/main/notebooks">notebooks folder </a>.
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  </p>
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  </p>
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  <h2>Duplicate the Space to run your own instance</h2>
 
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  <div class="left-align">
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  <h2>What's covered?</h2>
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  <p>Currently this Space has notebooks covering the following topics:</p>
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+ <h3>Creating synthetic text similarity datasets</h3>
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  <p>
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+ A set of notebooks covering the steps for creating a synthetic dataset for
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  fine-tuning a sentence similarity model. These notebooks cover:
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  </p>
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  <ul>
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  <li>
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  How to do structured generation using the
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+ <a href="https://github.com/outlines-dev/outlines" target="_blank">outlines</a> library
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  to have more control on the outputs generated by a LLM.
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  </li>
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  <li>
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  How to use
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+ <a href="https://docs.llamaindex.ai/en/stable/" target="_blank">Llama-index</a> to chunk
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  texts to fit into the context length of sentence embedding models.
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+ </li>
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+ <li>
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+ Using <a href="https://github.com/vllm-project/vllm" target="_blank">vLLM</a> to
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  efficiently create a dataset that can be used to fine-tune a Sentence
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  similarity model.
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  </li>
 
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  <div class="center-align">
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  <h2>Using the Space</h2>
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  <p>
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+ To use this Space, you should <a href="https://huggingface.co/spaces/davanstrien/synthetic-data-workshop?duplicate=true" target="_blank">duplicate it</a>.
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  To ensure your work is saved it's suggested to enable persistent storage for your Space.
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  To start, you may want to use a smaller GPU like the T4 and switch out to a bigger GPU when you want to run larger LLMs or generate more data.
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  <b>Reminder</b> you can preview the notebooks in the Space without running
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+ them. You can find the Jupyter Notebooks in the <a href="https://huggingface.co/spaces/davanstrien/synthetic-data-workshop/tree/main/notebooks" target="_blank">notebooks folder </a>.
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  </p>
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  </p>
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  <h2>Duplicate the Space to run your own instance</h2>