semvec/pypi-packages huggingface dataset:
gats-torch 0.0.1
gats - Pytorch
License: MIT
Requires Python: >=3.6,<4.0
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# GATS
Implementation of GATS from the paper: "GATS: Gather-Attend-Scatter" in pytorch and zeta.


## Install
`pip install gats`

## Usage


# Citation
```bibtex
@misc{zolna2024gats,
    title={GATS: Gather-Attend-Scatter}, 
    author={Konrad Zolna and Serkan Cabi and Yutian Chen and Eric Lau and Claudio Fantacci and Jurgis Pasukonis and Jost Tobias Springenberg and Sergio Gomez Colmenarejo},
    year={2024},
    eprint={2401.08525},
    archivePrefix={arXiv},
    primaryClass={cs.AI}
}
```

# License
MIT
pycounts-ramg23 0.1.0
Calculate words counts in a text file!
License: MIT
Requires Python: >=3.9

# pycounts_ramg23

Calculate words counts in a text file!

## Installation

```bash
$ pip install pycounts_ramg23
```

## Usage

`pycounts_ramg23` can be used to count words in a text file and plot results as follows:

```python
from pycounts_ramg23.pycounts_ramg23 import count_words
from pycounts_ramg23.plotting import plot_words
import matplotlib.pyplot as plot

file_path = "test.txt"  # path to your file_path
counts = count_words(file_path)
fig = plot_words(counts,n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_ramg23` was created by Rafael Montoya. It is licensed under the terms of the MIT license.

## Credits

`pycounts_ramg23` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
subtitle-utils 1.0.0
Subtilte Conversion utils - ass2srt vtt2bcc srt2bcc ass2bcc and more
License: MIT
Requires Python: <3.12,>=3.8

# subtitle_utils

![cover](https://raw.githubusercontent.com/sudoskys/subtitle_utils/main/src/cover.jpg)

<p align="center">
  <img src="https://img.shields.io/badge/Python-3.8|9|10|11-green" alt="Python" >
  <img src="https://img.shields.io/pypi/dm/subtitle_utils.svg" alt="Download">
</p>

Subtilte Conversion Utils - ass2srt vtt2bcc srt2bcc ass2bcc and more!

## Install 🥽

```
pip install -U subtitle_utils
```

## Usage ☕️

```python
from subtitle_utils import get_method, show_available, srt2bcc

print("Available methods:")
print(show_available())

with open("test.srt", 'r') as file_io:
    test_result = get_method(method="srt2bcc")(content=file_io)
    print(test_result)

_result = srt2bcc(content="1\n00:00:00,000 --> 00:00:01,000\nHello World")
print(_result)
```
cloudeasy 0.2.2
Some proxy for alicloud operation based on raw alicloud tea api
License: MIT
Requires Python: >=3.8,<4.0

# cloudeasy

[![Build](https://github.com/calmzhu/pycloudeasy/actions/workflows/build.yaml/badge.svg?branch=main)](https://github.com/calmzhu/pycloudeasy/actions/workflows/build.yaml)
[![Coverage](https://codecov.io/github/calmzhu/pycloudeasy/branch/main/graph/badge.svg)](https://app.codecov.io/github/calmzhu/pycloudeasy)
[![Python>=3.10](https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12-blue)](https://www.python.org)

## Description

A Friendly sdk based on raw api for
- alibaba cloud
- github

## Install

pip install cloudeasy

## Usage:

See [test case](https://github.com/calmzhu/pycloudeasy/tree/main/test) for examples