Contributions

app.py

@@ -21,7 +21,14 @@ The models were trained on a dataset comprising of [1 Billion+ training corpus](
 In addition, we trained [20 models](https://huggingface.co/flax-sentence-embeddings) focused on general-purpose, QuestionAnswering and Code search.
 You can view our models [here](https://huggingface.co/flax-sentence-embeddings)
 
-To evaluate the [flax-sentence-embeddings](https://huggingface.co/flax-sentence-embeddings) *Sentence Similarity models* for *Gender Bias based on stereotypical occupations*, we created an *evaluation set* which can be found [here](https://huggingface.co/datasets/manandey/Gender_Bias_Evaluation)
+## Contributions
+
+- 20 sentence embedding models that can be utilized for Sentence Simliarity / Asymmetric QA / Search / Clustering.
+- 8 Datasets from Stackexchange and StackOverflow, PAWS, Gender Evaluation formatted and uploaded to HuggingFace Hub.
+- Achieve SOTA on multiple general purpose Sentence Similarity evaluation tasks by utilizing large TPU memory to maximize
+ customized Contrastive Loss.
+- Gender Bias Demonstration that explores inherent bias in general purpose datasets.
+- Search / Clustering Demonstration that showcases real-world use-cases for Sentence Embeddings.
 
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