semvec/pypi-packages huggingface dataset:
bannerutils 1.1.1
Advanced ASCII Banner Generator.
Requires Python: >=3.6

# ASCII Banner Generator

## Overview
The **ASCII Banner Generator** is a command-line tool that converts text into stylish ASCII art banners. It supports multiple font styles, text alignment, and width customization. The tool is inspired by TAAG and utilizes the **pyfiglet** library for rendering text.

## Features
- Convert text into ASCII banners using a variety of fonts.
- Supports different text alignments (left, center, right).
- Adjustable banner width for better formatting.
- Copy generated banners directly to the clipboard.
- List available fonts with descriptions.

## Requirements
This script requires **Python 3.x** and the following dependencies:
- `pyfiglet` (for ASCII text rendering)
- `pyperclip` (for clipboard functionality)
- `argparse` (for command-line argument parsing)

If not installed, the script will automatically attempt to install missing packages.

## Installation
You can install the tool via **pip** or **GitHub**.

### Install via pip:
```sh
pip install bannerutils
```

### Install from GitHub:
1. Clone this repository:
   ```sh
   git clone https://github.com/jfrzz/bannerutils.git
   ```
2. Navigate to the directory:
   ```sh
   cd ascii-banner-generator
   ```
3. Run the script:
   ```sh
   python banner.py --help
   ```

## Usage
Basic command format:
```sh
python banner.py "Your Text Here" [-f FONT] [-w WIDTH] [-a ALIGN] [--fonthelp]
```

### Example Commands
1. Generate a simple ASCII banner:
   ```sh
   python banner.py "Hello, World!"
   ```
2. Use a specific font:
   ```sh
   python banner.py "Hello" -f slant
   ```
3. Adjust banner width:
   ```sh
   python banner.py "Wide Text" -w 100
   ```
4. Center-align text:
   ```sh
   python banner.py "Centered" -a center
   ```
5. List available fonts with descriptions:
   ```sh
   python banner.py --fonthelp
   ```

## Available Fonts
The tool supports various fonts, including:
- **slant**: Slanted letters for a stylish effect.
- **big**: Large and bold text.
- **bubble**: Rounded bubble-like letters.
- **digital**: Digital clock-style font.
- **gothic**: Fancy gothic-style text.
- **isometric**: Multiple 3D isometric variations.
- **starwars**: Inspired by Star Wars title fonts.
- And many more!

To see the full list, run:
```sh
python -m pyfiglet -l
```

## Clipboard Support
After generating the banner, the script prompts you to copy it to the clipboard. Simply enter `y` to copy or `n` to skip.

## License
This project is open-source and available under the MIT License.

## Author
Created by **[@JfrzxCode]**

---
check-model-config 0.1.0
A tool to validate transformer model configurations
Requires Python: >=3.9
Keywords: llm, pytest, transformers, validation

# check-model-config

A validation tool for transformer model configurations that helps identify inconsistencies between model configs, weights, and tokenizers.

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)

## Overview

`check-model-config` is a CLI tool that performs comprehensive validation checks on transformer models to ensure their configurations are consistent with their weights and tokenizers. It helps identify potential issues that could affect model performance or behavior.

The tool is particularly useful for:
- Model developers who want to ensure their published models have consistent configurations
- Users who want to validate models before using them in production
- Researchers working with modified or custom models who need to verify configuration integrity

## Installation

```bash
pip install check-model-config
```

## Usage

### Basic Usage

Run the validation tests on a model:

```bash
check-model-config --model openai/gpt2
```

You can use either a Hugging Face model ID or a local directory path:

```bash
check-model-config --model ./path/to/local/model
```

### Skip Weight-Dependent Tests

For faster validation or when working with very large models, you can skip tests that require loading model weights:

```bash
check-model-config --model meta-llama/Llama-2-70b --load-weights=False
```

## Validation Tests

The tool runs the following validation checks:

- **Vocabulary Size Consistency**: Verifies that vocab_size in config matches embedding weights, lm_head weights, and tokenizer
- **Hidden Size Consistency**: Ensures hidden dimensions match across weights and config
- **Layer Count Validation**: Checks that layer counts in config match actual weights
- **Attention Mechanism**: Validates KQV projections and attention output dimensions
- **MLP Layers**: Checks feed-forward network dimensions and activation functions
- **Tied Embeddings**: Verifies embedding tying configuration matches implementation
- **Position Embeddings**: Validates position embedding configuration and implementation
- **Mixture of Experts**: Checks MoE configurations for models that use experts
- **Window Layers**: Validates sliding window attention configurations

## Requirements

- Python 3.9+
- PyTorch 2.5.1+
- Transformers 4.47.1+
- Accelerate 1.2.0+

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.