Fix format issues

docs/src/configuration.md

@@ -41,7 +41,10 @@ batch: batch_size
 
 By default, FENN will look for a configuration file named `fenn.yaml` in the current directory. If you would like to use a different name, a different location, or have multiple configuration files for different configurations, you can set the `config_file` property of FENN to the path of your file. You must assign the filename before calling `run()`:
 
+
+```
 app = FENN()
 app.config_file = "my_file.yaml"
 ...
 app.run()
+```

docs/src/contributing.md

@@ -4,12 +4,12 @@ Welcome to the **fenn** project! This guide explains how to prepare your changes
 
 ## Initial Checks
 
-Before you start coding, read the main `README.md` and the [documentation](https://pyfenn.org/) to understand the project goals, basic usage, and current roadmap. [web:0]
+Before you start coding, read the main `README.md` and the [documentation](https://pyfenn.org/) to understand the project goals, basic usage, and current roadmap.  
 
 > **Tip**  
-> If you are unsure what to work on or want feedback on an idea, start a conversation on the project’s Discord server or in the GitHub discussion thread linked from the README so the maintainers can help you scope a useful contribution. [web:0]
+> If you are unsure what to work on or want feedback on an idea, start a conversation on the project’s Discord server or in the GitHub discussion thread linked from the README so the maintainers can help you scope a useful contribution.  
 
-Whenever possible, prefer small, focused changes over very large pull requests. If you plan a bigger feature or refactor, discuss it first to confirm that it fits the project direction. [web:0]
+Whenever possible, prefer small, focused changes over very large pull requests. If you plan a bigger feature or refactor, discuss it first to confirm that it fits the project direction. 
 
 ## Basic Git Workflow
 
@@ -58,7 +58,7 @@ Once your branch is ready: [web:0]
 
 ## Reporting Issues and Getting Help
 
-If you find a bug or have a feature request but do not plan to implement it yourself: [web:0]
+If you find a bug or have a feature request but do not plan to implement it yourself:  
 
 - Open a GitHub issue with a clear description of the problem or idea.  
 - For bugs, describe the expected behavior, the actual behavior, and how to reproduce it (include versions and environment details when possible).  

docs/src/index.md

@@ -9,7 +9,7 @@
 
 **Stop writing boilerplate. Start training.**
 
-FENN is a lightweight Python framework that automates the “boring stuff” in Machine Learning projects so you can focus on the model. It handles configuration parsing, logging setup, and experiment tracking in a minimal, opinionated way.
+FENN is a lightweight Python framework that automates the **boring stuff** in Machine Learning projects so you can focus on the model. It handles configuration parsing, logging setup, and experiment tracking in a minimal, opinionated way.
 
 > **See also**  
 > Source code available at: <https://github.com/pyfenn/fenn>

docs/src/quickstart.md

@@ -1,9 +1,9 @@
 # Quickstart
 
-This section provides a guided overview of setting up FENN in a new environment, defining a minimal project structure, and executing an initial experiment through a configuration-driven entrypoint. By the end of this section, you will have a functioning Python script that relies on `fenn.yaml` for configuration rather than hardcoded parameters. [web:0]
+This section provides a guided overview of setting up FENN in a new environment, defining a minimal project structure, and executing an initial experiment through a configuration-driven entrypoint. By the end of this section, you will have a functioning Python script that relies on `fenn.yaml` for configuration rather than hardcoded parameters. 
 
 ## Installation
 
-FENN is distributed as a standard Python package and can be installed from PyPI. It is recommended to use a virtual environment (`venv` or `conda`) to keep your project dependencies isolated. [web:0]
+FENN is distributed as a standard Python package and can be installed from PyPI. It is recommended to use a virtual environment (`venv` or `conda`) to keep your project dependencies isolated. 
 
 

docs/src/wandb.md

@@ -26,18 +26,18 @@ FENN uses a `fenn.yaml` file to centralize project configuration (training, logg
 
 Minimal example of `fenn.yaml` with W&B support:
 
+```
 wandb:
 entity: your_wandb_account
 key: your_wandb_key
-
-text
+```
 
 ## 3. Running an experiment
 
 Once the `fenn.yaml` file has been configured, including the `wandb` section, you can start an experiment by running your FENN entrypoint script as a standard Python program:
 
-python main.py
+`python main.py`
+
 
-text
 
 During execution, the script reads the configuration from `fenn.yaml`, initializes the W&B client, and sends configuration data and training metrics to your W&B project. When the run completes, you can open <https://wandb.ai>, navigate to the configured project, and inspect dashboards with loss and accuracy curves, stored experiment configurations, and any saved files such as models and logs.