Project for traing and research LLAMA model os Stack Overflow data for generative Q&A
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for details
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── src <- Source code for use in this project.
| └──sft
| ├── __init__.py <- Makes src a Python module
│ │
| ├──config <- Config to train and test model
| | └── test_config.yaml
| |
│ ├── data <- Scripts to download or generate data
│ │ └── make_inference_dataset.py
│ │
│ │
│ ├── models <- Methods to organise eval and train steps
│ │ ├── test_model.py
│ │ └── train_model.py
│ │
│ ├── scripts <- Scripts to train and test models and than use to make predictons
│ | └── test_script.py
│ │
│ └── utils <- Helpful utils to loging, saving and loading something
│ ├── load_model.py
│ ├── wandb_log.py
│ └── save_csv.py
│
└── tox.ini <- tox file with settings for running tox; see tox.readthedocs.io
Project based on the cookiecutter data science project template. #cookiecutterdatascience