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# Protein Inverse Folding
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We finetune the [AIDO.Protein-16B](https://huggingface.co/genbio-ai/AIDO.DNA-16B) model with LoRA on the [CATH 4.2](https://pubmed.ncbi.nlm.nih.gov/9309224/) benmark dataset. We use the same train, validation, and test splits used by the previous studies, such as [LM-Design](https://arxiv.org/abs/2302.01649), and [DPLM](https://arxiv.org/abs/2402.18567). Current version of ModelGenerator contains the inference pipeline for protein inverse folding. Experimental pipeline on other datasets (both training and testing) will be included in the future.
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#### Setup
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Install [Model Generator](https://github.com/genbio-ai/modelgenerator).
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- It is **required** to use [docker](https://www.docker.com/101-tutorial/) to run our inverse folding pipeline.
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- Please set up a docker image using our provided [Dockerfile](https://github.com/genbio-ai/ModelGenerator/blob/main/Dockerfile) and run the inverse folding inference from within the docker container.
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# Protein Inverse Folding
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We finetune the [AIDO.Protein-16B](https://huggingface.co/genbio-ai/AIDO.DNA-16B) model with LoRA on the [CATH 4.2](https://pubmed.ncbi.nlm.nih.gov/9309224/) benmark dataset. We use the same train, validation, and test splits used by the previous studies, such as [LM-Design](https://arxiv.org/abs/2302.01649), and [DPLM](https://arxiv.org/abs/2402.18567). Current version of ModelGenerator contains the inference pipeline for protein inverse folding. Experimental pipeline on other datasets (both training and testing) will be included in the future.
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#### Setup:
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Install [Model Generator](https://github.com/genbio-ai/modelgenerator).
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- It is **required** to use [docker](https://www.docker.com/101-tutorial/) to run our inverse folding pipeline.
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- Please set up a docker image using our provided [Dockerfile](https://github.com/genbio-ai/ModelGenerator/blob/main/Dockerfile) and run the inverse folding inference from within the docker container.
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