gbyuvd
/

ChemEmbed-v01

Sentence Similarity

sentence-transformers

feature-extraction

Generated from Trainer

dataset_size:1,183,174

loss:CosineSimilarityLoss

text-embeddings-inference

Inference Endpoints

Model card Files Files and versions Community

gbyuvd commited on Jun 27, 2024

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@@ -185,7 +185,7 @@ print(similarities.shape)
 For now, the model might be ineffective in embedding synthetic drugs, since it is still trained on just natural products. Also, the tokenizer used is still uncustomized one.
 ## Testing Generated Embeddings' Clusters
-The plot below show how the model's embeddings (at this stage) cluster different classes of compounds, compared to using MACCS fingerprints.
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/667da868d653c0b02d6a2399/c8_5IWjPgbrGY0Z9-ZHop.png)

 For now, the model might be ineffective in embedding synthetic drugs, since it is still trained on just natural products. Also, the tokenizer used is still uncustomized one.
 ## Testing Generated Embeddings' Clusters
+The plot below shows how the model's embeddings (at this stage) cluster different classes of compounds, compared to using MACCS fingerprints.
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/667da868d653c0b02d6a2399/c8_5IWjPgbrGY0Z9-ZHop.png)