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Trent
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app.py
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@@ -15,7 +15,8 @@ menu = st.sidebar.radio("", options=["Contributions & Evaluation", "Sentence Sim
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st.markdown('''
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We trained multiple general-purpose flax-sentence-embeddings models starting from different BERT models including
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distilroberta, mpnet and MiniLM-l6. They were trained using Siamese network configuration with custom **Contrastive Loss**
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inspired by OpenAI CLIP. The models were trained on a dataset comprising of [1 Billion+ training corpus](https://huggingface.co/flax-sentence-embeddings/all_datasets_v4_MiniLM-L6#training-data) with the v3 setup.
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st.markdown('''
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Sentence Transformers is a set of Frameworks & Models that are trained to generate Sentence Embeddings. Generated
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Sentence Embeddings can be used for Sentence Simliarity / Asymmetric QA / Semantic Search / Clustering among other tasks.
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We trained multiple general-purpose flax-sentence-embeddings models starting from different BERT models including
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distilroberta, mpnet and MiniLM-l6. They were trained using Siamese network configuration with custom **Contrastive Loss**
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inspired by OpenAI CLIP. The models were trained on a dataset comprising of [1 Billion+ training corpus](https://huggingface.co/flax-sentence-embeddings/all_datasets_v4_MiniLM-L6#training-data) with the v3 setup.
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