Commit f61c390d authored by Ines Filipa Fernandes Ramos's avatar Ines Filipa Fernandes Ramos
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Update README.md

parent f7badbc7
......@@ -5,19 +5,16 @@ Repository of code developed to implement inception loops ([Walker et al. 2019 N
To install the environment with the modified code and custom code necessary to use the notebooks, follow the followig steps after installing conda.
Use the terminal or an Anaconda Prompt for the following steps:
1. Create the environment from the environment.yml file:
conda env create -f environment.yml
1. Create the environment from the environment.yml file:
conda env create -f environment.yml
The first line of the yml file sets the new environment's name.
2. Activate the new environment:
2. Activate the new environment:
conda activate myenv
3. Verify that the new environment was installed correctly:
conda env list
You can also use conda info --envs.
3. Verify that the new environment was installed correctly:
conda env list
You can also use conda info --envs
To train the CNN for the inception loop, refer to the notebook_V1_core_CNN.ipynb to use a network with a pre-trained core on V1 neuron responses from [Lurz et al. 2020 bioRxiv](https://www.biorxiv.org/content/10.1101/2020.10.05.326256v2)), to notebook_task_driven_core.ipynb to use a network with a pre-trained image classification core from TorchVision models or to notebook_train_core_CNN.ipynb to train the core from scratch. To generate MEIs, refer to notebook_MEI_gen.ipynb.
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