Update README.md

README.md

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-# scarf
+# SCARF - PyTorch
+
+This repo reproduces the SCARF (Self-Supervised Contrastive Learning Using Random Feature Corruption) framework for self-supervised learning with tabular data.
+
+*Authors: Dara Bahri, Heinrich Jiang, Yi Tay, Donald Metzler*
+
+*Reference: Bahri, Dara, et al. "Scarf: Self-supervised contrastive learning using random feature corruption." arXiv preprint arXiv:2106.15147 (2021).*
+
+Original paper: https://research.google/pubs/scarf-self-supervised-contrastive-learning-using-random-feature-corruption/
+
+Original repo: --
 
 ## Install
 
-Create a virtual environment with Python >= 3.11 and install from git:
+Clone this repository, create a new Conda environment and 
 
 ```bash
-pip install git+https://github.com/chris-santiago/scarf.git
+git clone https://github.com/chris-santiago/scarf.git
+conda env create -f environment.yml
+cd scarf
+pip install -e .
 ```
 
 ## Use
 
+### Prerequisites
+
+#### Hydra
 
-## Documentation
+This project uses [Hydra](https://hydra.cc/docs/intro/) for managing configuration CLI arguments. See `scarf/conf` for full
+configuration details.
+
+#### Task
+
+This project uses [Task](https://taskfile.dev/) as a task runner. Though the underlying Python
+commands can be executed without it, we recommend [installing Task](https://taskfile.dev/installation/)
+for ease of use. Details located in `Taskfile.yml`.
+
+#### Current commands
+
+```bash
+> task -l
+task: Available tasks for this project:
+* check-config:       Check Hydra configuration
+* compare:            Compare using linear baselines
+* train:              Train a model
+* wandb:              Login to Weights & Biases
+```
+
+Example: Train model and for `adult-income` dataset experiment
+
+*The `--` forwards CLI arguments to Hydra.*
+
+```bash
+task train -- experiment=income
+```
+
+#### PDM
+
+This project was built using [this cookiecutter](https://github.com/chris-santiago/cookie) and is
+setup to use [PDM](https://pdm.fming.dev/latest/) for dependency management, though it's not required
+for package installation.
+
+#### Weights and Biases
+
+This project is set up to log experiment results with [Weights and Biases](https://wandb.ai/). It
+expects an API key within a `.env` file in the root directory:
+
+```toml
+WANDB_KEY=<my-super-secret-key>
+```
 
-Documentation hosted on Github Pages: [https://chris-santiago.github.io/scarf/](https://chris-santiago.github.io/scarf/)
+Users can configure different logger(s) within the `conf/trainer/default.yaml` file.