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@@ -22,7 +22,7 @@ We provide genomic language models fine-tuned for the following tasks:
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  - **Anti-microbial resistance gene identification**
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  - **Pathogenicity detection**
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- See [code](github.com/jhuapl-bio/microbert) for details on fine-tuning, evaluation, and implementation.
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  These are the official models implemented in [Evaluating the Effectiveness of Parameter-Efficient Fine-Tuning in Genomic Classification Tasks](https://www.biorxiv.org/content/10.1101/2025.08.21.671544v1) and []()
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@@ -73,8 +73,8 @@ We provide the following available models for use.
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  - `pathogenicity/nucleotide-transformer-v2-50m-multi-species-DeepSim-viral`
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  To use these models, download the directories available here.
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- You must also follow the installation instructions available at our [GitHub Repo](github.com/jhuapl-bio/microbert).
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- There are two available modes of operation: setup from source code and setup from Docker.
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  Given that you have followed the setup instructions from source code and have downloaded the model directories here, here is sample code to run inference:
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  ```
 
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  - **Anti-microbial resistance gene identification**
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  - **Pathogenicity detection**
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+ See [code](https://github.com/jhuapl-bio/microbert) for details on fine-tuning, evaluation, and implementation.
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  These are the official models implemented in [Evaluating the Effectiveness of Parameter-Efficient Fine-Tuning in Genomic Classification Tasks](https://www.biorxiv.org/content/10.1101/2025.08.21.671544v1) and []()
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  - `pathogenicity/nucleotide-transformer-v2-50m-multi-species-DeepSim-viral`
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  To use these models, download the directories available here.
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+ You should also follow the installation instructions available at our [code](https://github.com/jhuapl-bio/microbert).
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+ There are two available modes of operation: setup from source code and setup from [docker](docker hub link)
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  Given that you have followed the setup instructions from source code and have downloaded the model directories here, here is sample code to run inference:
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  ```