Update README.md

README.md

@@ -7,29 +7,64 @@ base_model:
 We fully finetune the [AIDO.RNA-1.6B](https://huggingface.co/genbio-ai/AIDO.RNA-1.6B) model on the single-state split from [Das _et al._](https://www.nature.com/articles/nmeth.1433) already processed by [Joshi _et al._](https://arxiv.org/abs/2305.14749). We use the same train, validation, and test splits used by their method [gRNAde](https://arxiv.org/abs/2305.14749). Current version of ModelGenerator contains the inference pipeline for RNA inverse folding. Experimental pipeline on other datasets (both training and testing) will be included in the future.
 
 #### Setup:
-Install [Model Generator](https://github.com/genbio-ai/modelgenerator). 
+Install [ModelGenerator](https://github.com/genbio-ai/modelgenerator). 
 - It is **required** to use [docker](https://www.docker.com/101-tutorial/) to run our inverse folding pipeline.
-- 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.
-
-#### Running inference:
-
-- Set the environment variable for ModelGenerator's data directory (**Note:** the docker image with our provided [Dockerfile](https://github.com/genbio-ai/ModelGenerator/blob/main/Dockerfile) will already have it set):
+- 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. 
+  - Here is an example bash script to set up and access a docker container:
     ```
-    export MGEN_DATA_DIR=~/mgen_data # or any other local directory of your choice, if you would like to change it inside [Dockerfile](https://github.com/genbio-ai/ModelGenerator/blob/main/Dockerfile)
+    # clone the ModelGenerator repository
+    git clone https://github.com/genbio-ai/ModelGenerator.git
+    # cd to "ModelGenerator" folder where you should find the "Dockerfile"
+    cd ModelGenerator
+    # create a docker image
+    docker build -t aido .
+    # create a local folder as ModelGenerator's data directory
+    mkdir -p $HOME/mgen_data
+    # run a container
+    docker run -d --runtime=nvidia -it -v "$(pwd):/workspace" -v "$HOME/mgen_data:/mgen_data" aido /bin/bash
+    # find the container ID
+    docker ps # this will print the running containers and their IDs
+    # execute the container with ID=<container_id>
+    docker exec -it <container_id> /bin/bash  # now you should be inside the docker container
+    # test if you can access the nvidia GPUs
+    nvidia-smi # this should print the GPUs' details
     ```
+- Execute the following steps from **within** the docker container you just created.
+
+#### Download model checkpoints:
 
 - Download the `model.ckpt` checkpoint from [here](https://huggingface.co/genbio-ai/AIDO.RNAIF-1.6B/blob/main/model.ckpt). Place it inside the local directory `${MGEN_DATA_DIR}/modelgenerator/huggingface_models/rna_inv_fold/AIDO.RNAIF-1.6B`.
+  
+  **Alternatively**, you can simply run the following script to do this:
+  ```
+  mkdir -p ${MGEN_DATA_DIR}/modelgenerator/huggingface_models/rna_inv_fold/AIDO.RNAIF-1.6B
+  wget -P ${MGEN_DATA_DIR}/modelgenerator/huggingface_models/rna_inv_fold/AIDO.RNAIF-1.6B https://huggingface.co/genbio-ai/AIDO.RNAIF-1.6B/resolve/main/model.ckpt
+  ```
 
-- Download the gRNAde checkpoint named `gRNAde_ARv1_1state_das.h5` from [here](https://github.com/chaitjo/geometric-rna-design/blob/main/checkpoints/gRNAde_ARv1_1state_all.h5). Place it inside the directory `${MGEN_DATA_DIR}/modelgenerator/other_models/rna_inv_fold/`.
+- Download the gRNAde checkpoint named `gRNAde_ARv1_1state_das.h5` from the [huggingface-hub](https://huggingface.co/genbio-ai/AIDO.RNAIF-1.6B/blob/main/other_models/gRNAde_ARv1_1state_all.h5) ***or*** the [original source](https://github.com/chaitjo/geometric-rna-design/blob/main/checkpoints/gRNAde_ARv1_1state_all.h5). Place it inside the directory `${MGEN_DATA_DIR}/modelgenerator/other_models/rna_inv_fold/`.
+  
+  **Alternatively**, you can do it by simply running the following script:
+  ```
+  mkdir -p ${MGEN_DATA_DIR}/modelgenerator/other_models/rna_inv_fold/
+  wget -P ${MGEN_DATA_DIR}/modelgenerator/other_models/rna_inv_fold/ https://huggingface.co/genbio-ai/AIDO.RNAIF-1.6B/resolve/main/other_models/gRNAde_ARv1_1state_all.h5
+  ```
 
-- Download the data preprocessed by [Joshi _et al._](https://arxiv.org/abs/2305.14749). Mainly download these two files: [processed.pt.zip](https://drive.google.com/file/d/1gcUUaRxbGZnGMkLdtVwAILWVerVCbu4Y/view) and [processed_df.csv](https://drive.google.com/file/d/1lbdiE1LfWPReo5VnZy0zblvhVl5QhaF4/view). Place them inside the directory `${MGEN_DATA_DIR}/modelgenerator/datasets/rna_inv_fold/raw_data/`. 
+#### Download data:
+- Download the data preprocessed by [Joshi _et al._](https://arxiv.org/abs/2305.14749). Mainly download these two files: processed.pt.zip ([huggingface-hub](https://huggingface.co/datasets/genbio-ai/rna-inverse-folding/blob/main/processed.pt.zip), [original source](https://drive.google.com/file/d/1gcUUaRxbGZnGMkLdtVwAILWVerVCbu4Y/view)) and processed_df.csv ([huggingface-hub](https://huggingface.co/datasets/genbio-ai/rna-inverse-folding/blob/main/processed_df.csv), [original source](https://drive.google.com/file/d/1lbdiE1LfWPReo5VnZy0zblvhVl5QhaF4/view)). Place them inside the directory `${MGEN_DATA_DIR}/modelgenerator/datasets/rna_inv_fold/raw_data/`. Please refer to [this link](https://github.com/chaitjo/geometric-rna-design/tree/main?tab=readme-ov-file#downloading-and-preparing-data) for details about the dataset and its preprocessing.
 
+  **Alternatively**, you run the following script to do it:
+  ```
+  mkdir -p ${MGEN_DATA_DIR}/modelgenerator/datasets/rna_inv_fold/raw_data/
+  wget -P ${MGEN_DATA_DIR}/modelgenerator/datasets/rna_inv_fold/raw_data/ https://huggingface.co/datasets/genbio-ai/rna-inverse-folding/resolve/main/processed.pt.zip
+  wget -P ${MGEN_DATA_DIR}/modelgenerator/datasets/rna_inv_fold/raw_data/ https://huggingface.co/datasets/genbio-ai/rna-inverse-folding/resolve/main/processed_df.csv
+  ```
 
-- From your terminal, change directory to `ModelGenerator/experiments/AIDO.RNA/rna_inverse_folding` and run the script `rna_inverse_folding.sh`:
+#### Run inference:
+- From your terminal, run the script `rna_inverse_folding.sh`:
     ```
-    cd experiments/AIDO.RNA/rna_inverse_folding
     bash rna_inverse_folding.sh
     ```
+- **Note:** Multi-GPU inference for inverse folding is not currently supported and will be included in the future.
 
 #### Outputs:
 - The evaluation score will be printed on the console.