zjunlp
/

MolGen-large-opt

text2text-generation

molecular language model

molecule optimization

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Yin Fang commited on Feb 19, 2023

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@@ -15,7 +15,7 @@ With a training corpus of over 100 million molecules in SELFIES representation,
 Specifically, MolGen-large employs a bidirectional Transformer as its encoder and an autoregressive Transformer as its decoder.
 Through its carefully designed multi-task molecular prefix tuning (MPT), MolGen-large-opt can generate molecules with desired properties, making it a valuable tool for molecular optimization.
-![image.png](./model.png)
 ## Intended uses
 You can use the fine-tuned model for molecule optimization for downstream tasks. See the [repository](https://github.com/zjunlp/MolGen) to look for fine-tune details on a task that interests you.

 Specifically, MolGen-large employs a bidirectional Transformer as its encoder and an autoregressive Transformer as its decoder.
 Through its carefully designed multi-task molecular prefix tuning (MPT), MolGen-large-opt can generate molecules with desired properties, making it a valuable tool for molecular optimization.
+![image.png](./molgen.png)
 ## Intended uses
 You can use the fine-tuned model for molecule optimization for downstream tasks. See the [repository](https://github.com/zjunlp/MolGen) to look for fine-tune details on a task that interests you.