Upload README.md

README.md

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+## Introduction
+<p align="center">
+    <br>
+    <img src="assets/FAPM.png"/>
+    <br>
+<p>  
+    
+Huggingface repo: *https://huggingface.co/wenkai/FAPM/*  
+
+## Installation
+
+1. (Optional) Creating conda environment
+
+```bash
+conda create -n lavis python=3.8
+conda activate lavis
+```
+ 
+2. for development, you may build from source
+
+```bash
+git clone https://github.com/xiangwenkai/FAPM.git
+cd FAPM
+pip install -e .
+
+pip install Biopython
+pip install fair-esm
+```
+
+### Datasets
+#### 1.raw dataset
+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.  
+The domain level protein dataset we used are avaliable at *https://ftp.ebi.ac.uk/pub/databases/interpro/releases/95.0/protein2ipr.dat.gz*  
+In this respository, We provide the experimental train/val/test sets of Swiss-Prot, which are avaliable at data/swissprot_exp  
+#### 2.ESM2 embeddings  
+Source code for ESM2 embeddings generation: *https://github.com/facebookresearch/esm*  
+The generation command:  
+```bash
+conda activate FAPM
+python esm_scripts/extract.py esm2_t36_3B_UR50D you_path/protein.fasta you_path_to_save_embedding_files --repr_layers 36 --truncation_seq_length 1024 --include per_tok
+```
+Example:
+```
+conda activate FAPM
+python esm_scripts/extract.py esm2_t36_3B_UR50D data/fasta/example.fasta data/emb_esm2_3b --repr_layers 36 --truncation_seq_length 1024 --include per_tok
+```  
+
+The default path to save embedding files is **data/emb_esm2_3b**
+
+## Pretraining language models  
+Source: *https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B*
+
+## Training
+data config: lavis/configs/datasets/protein/GO_defaults_cap.yaml  
+stage1 config: lavis/projects/blip2/train/protein_pretrain_stage1.yaml  
+stage1 training command: run_scripts/blip2/train/protein_pretrain_domain_stage1.sh  
+stage2 config: lavis/projects/blip2/train/protein_pretrain_stage2.yaml  
+stage2 training/finetuning command: run_scripts/blip2/train/protein_pretrain_domain_stage2.sh  
+
+## Trained models
+The models are avaliable at **https://huggingface.co/wenkai/FAPM/tree/main/model**  
+You can also download our trained models from google drive: *https://drive.google.com/drive/folders/1aA0eSYxNw3DvrU5GU1Cu-4q2kIxxAGSE?usp=drive_link*  
+
+## Testing
+config: lavis/projects/blip2/eval/caption_protein_eval.yaml  
+command: run_scripts/blip2/eval/eval_cap_protein.sh  
+
+## Inference example
+```
+python FAPM_inference.py \
+--model_path model/checkpoint_mf2.pth \
+--example_path data/emb_esm2_3b/P18281.pt \
+--device cuda \
+--prompt Acanthamoeba \
+--prop True
+```  
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