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+ ## Introduction
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+ <p align="center">
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+ <br>
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+ <img src="assets/FAPM.png"/>
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+ <br>
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+ <p>
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+
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+ ## Installation
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+
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+ 1. (Optional) Creating conda environment
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+ ```bash
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+ conda create -n lavis python=3.8
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+ conda activate lavis
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+ ```
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+ 2. for development, you may build from source
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+ ```bash
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+ git clone https://github.com/xiangwenkai/FAPM.git
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+ cd FAPM
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+ pip install -e .
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+ pip install Biopython
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+ pip install fair-esm
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+ ```
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+
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+ ### Datasets
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+ #### 1.raw dataset
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+ Raw data are avaliable at *https://ftp.uniprot.org/pub/databases/uniprot/previous_releases/release-2023_04/knowledgebase/*, this file is very large and need to be processed to get its name, sequence, GO label, function description and prompt.
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+ The domain level protein dataset we used are avaliable at *https://ftp.ebi.ac.uk/pub/databases/interpro/releases/95.0/protein2ipr.dat.gz*
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+ In this respository, We provide the experimental train/val/test sets of Swiss-Prot, which are avaliable at data/swissprot_exp
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+ #### 2.ESM2 embeddings
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+ Source code for ESM2 embeddings generation: *https://github.com/facebookresearch/esm*
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+ The generation command:
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+ ```bash
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+ python esm_scripts/extract.py esm2_t33_3B_UR50D you_path/protein.fasta you_path_to_save_embedding_files --repr_layers 36 --truncation_seq_length 1024 --include per_tok
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+ ```
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+ The default path to save embedding files in this respository is **data/emb_esm2_3b**
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+
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+ ## Pretraining language models
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+ Source: *https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B*
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+
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+ ## Training
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+ data config: lavis/configs/datasets/protein/GO_defaults_cap.yaml
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+ stage1 config: lavis/projects/blip2/train/protein_pretrain_stage1.yaml
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+ stage1 training command: run_scripts/blip2/train/protein_pretrain_domain_stage1.sh
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+ stage2 config: lavis/projects/blip2/train/protein_pretrain_stage2.yaml
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+ stage2 training/finetuning command: run_scripts/blip2/train/protein_pretrain_domain_stage2.sh
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+
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+ ## Trained models
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+ You can download our trained models from drive: *https://drive.google.com/drive/folders/1aA0eSYxNw3DvrU5GU1Cu-4q2kIxxAGSE?usp=drive_link*
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+
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+ ## Testing
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+ config: lavis/projects/blip2/eval/caption_protein_eval.yaml
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+ command: run_scripts/blip2/eval/eval_cap_protein.sh
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+
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+ ## Inference example
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+ We provide an example in **FAPM_inference.py**. You can change the example protein to you custom case
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