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app.py
CHANGED
@@ -34,11 +34,10 @@ with gr.Blocks() as demo:
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gr.HTML("""<center><h1 style='font-size:xx-large;'>πͺπΊ Euro City Recommender using Gemini & Gemma πͺπΊ</h1><br><h3>Gemini
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& Gemma Sprints 2024 submissions by Ashmi Banerjee. </h3></center> <br><p>We're testing the compatibility of
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Retrieval Augmented Generation (RAG) implementations with Google's <b>Gemma-2b-it</b> & <b>Gemini 1.0 Pro</b>
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models through HuggingFace and VertexAI respectively to generate travel recommendations. This early version (read
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quick and dirty implementation) aims to see if functionalities work smoothly. It relies on Wikipedia abstracts
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from 160 European cities to provide answers to your questions. Please be kind with it as it's a work in progress!
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</p> <br>Google Cloud credits are provided for this project.
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<p><b>Update: 12th April, 2024: <a href="https://huggingface.co/docs/text-generation-inference/en/supported_models"> HuggingFace TGI stopped Gemma support. Hence, only Gemini is supported now.</a></b></p>
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""")
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with gr.Group():
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gr.HTML("""<center><h1 style='font-size:xx-large;'>πͺπΊ Euro City Recommender using Gemini & Gemma πͺπΊ</h1><br><h3>Gemini
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& Gemma Sprints 2024 submissions by Ashmi Banerjee. </h3></center> <br><p>We're testing the compatibility of
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36 |
Retrieval Augmented Generation (RAG) implementations with Google's <b>Gemma-2b-it</b> & <b>Gemini 1.0 Pro</b>
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37 |
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models through HuggingFace and VertexAI, respectively, to generate travel recommendations. This early version (read
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quick and dirty implementation) aims to see if functionalities work smoothly. It relies on Wikipedia abstracts
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from 160 European cities to provide answers to your questions. Please be kind with it, as it's a work in progress!
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</p> <br>Google Cloud credits are provided for this project. </p>
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""")
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with gr.Group():
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