iliabenk/deep_learning_raja

Includes all homework assignments for deep learning Raja's course 2023-2024

Python

0

54 commits

updated May 28, 2024

See the code

README

How to run the project code:

  1. Install conda environment:
    1. cd mocha_code
    2. conda env create -f environment.yml
    3. conda activate mocha
    4. python -m spacy download en_core_web_sm
    5. python -m spacy download en_core_web_trf
  2. Go to the folder "mocha_code", which is the project's folder.
  3. Run the following python scripts, depending on what you want to achieve. A GPU with at least 16GB of memory is required.
    1. generate_images.py: will generate the images from the ~3200 captions
    2. generate.py: Will generate the captions with Mistral based on the available captions from GPT4
    3. generate_captions.py: Will generate captions using BLIP + MOCHa for the new dataset
    4. evaluate.py: Will evaluate the hallucination ratio using Mistral on the generated captions from generate_captions.py

iliabenk/deep_learning_raja

Includes all homework assignments for deep learning Raja's course 2023-2024

Python

0

54 commits

updated May 28, 2024

See the code

README

How to run the project code:

  1. Install conda environment:
    1. cd mocha_code
    2. conda env create -f environment.yml
    3. conda activate mocha
    4. python -m spacy download en_core_web_sm
    5. python -m spacy download en_core_web_trf
  2. Go to the folder "mocha_code", which is the project's folder.
  3. Run the following python scripts, depending on what you want to achieve. A GPU with at least 16GB of memory is required.
    1. generate_images.py: will generate the images from the ~3200 captions
    2. generate.py: Will generate the captions with Mistral based on the available captions from GPT4
    3. generate_captions.py: Will generate captions using BLIP + MOCHa for the new dataset
    4. evaluate.py: Will evaluate the hallucination ratio using Mistral on the generated captions from generate_captions.py