semvec/pypi-packages huggingface dataset:
pycounts-rory 1.0.0
A word count calculator
License: MIT
Requires Python: >=3.9

## Installation

```bash
$ pip install pycounts_rory
```

## Usage

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

```python
from pycounts_rory.pycounts_rory import count_words
from pycounts_rory.plotting import plot_words
import matplotlib.pyplot as plt

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

For full documentation see: [https://pycounts-rory.readthedocs.io/en/latest/](https://pycounts-rory.readthedocs.io/en/latest/)

## 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_rory` was created by Rory White. It is licensed under the terms of the MIT license.

## Credits

`pycounts_rory` was created with 
[`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and 
the `py-pkgs-cookiecutter` 
[template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-dsci524-shumlh 0.1.1
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9

# pycounts_dsci524_shumlh

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_dsci524_shumlh
```

## Usage

`pycounts_dsci524_shumlh` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_dsci524_shumlh.pycounts_dsci524_shumlh import count_words
from pycounts_dsci524_shumlh.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
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_dsci524_shumlh` was created by Tony Shum. It is licensed under the terms of the MIT license.

## Credits

`pycounts_dsci524_shumlh` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-cl 0.1.1
524 Assignment 1
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_cl

524 Assignment 1

## Installation

```bash
$ pip install pycounts_cl
```

## Usage

- Can count the number of characters from a given text file

## 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_cl` was created by Chun Li. It is licensed under the terms of the MIT license.

## Credits

`pycounts_cl` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
qwen 0.1.1
Qwen VL - Pytorch
License: MIT
Requires Python: >=3.6,<4.0
Keywords: artificial intelligence,attention mechanism,transformers

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


# Qwen-VL
My personal implementation of the model from "Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities", they haven't released model code yet sooo... 
For more details, please refer to the [full paper](https://doi.org/10.48550/arXiv.2308.12966).


# Install
`pip3 install qwen`

---

# Usage
```python

# Importing the necessary libraries
import torch
from qwen import Qwen

# Creating an instance of the Qwen model
model = Qwen()

# Generating random text and image tensors
text = torch.randint(0, 20000, (1, 1024))
img = torch.randn(1, 3, 256, 256)

# Passing the image and text tensors through the model
out = model(img, text)  # (1, 1024, 20000)

```

# Todo

- [ ] Position aware vision language adapter, compresses image features. Singer layer cross attention module inited randomly => group of trainable embeddings as query vectors + image features from the visual encoder as keys for cross attention ops => OUTPUT: compresses visual feature sequence to a fixed lnegth of 256, 2d absolute positional encodings are integrated into the cross attentions mechanisms query key pairs => compressed feature sequence of length of 256 => fed into decoder llm

- [ ] Bounding Boxes, for any given accurate bounding box, a norm process is applied in the range [0, 1000] and transformed into a string format (Xtope, Ytople)(Xottomright, Ybottomright) -> the string is tokenized as text and does not require positional vocabulary. Detection strings and regular text strings, two special tokens <box> and </box> are added to the beginning and end of the bounding box string. + another sed of special tokens (<ref> and </ref>) is introduced.

# Citations

Please use the following to cite this work:

```bibtex
@article{bai2023qwen,
  title={Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities},
  author={Bai, Jinze and Bai, Shuai and Yang, Shusheng and Wang, Shijie and Tan, Sinan and Wang, Peng and Lin, Junyang and Zhou, Chang and Zhou, Jingren},
  journal={arXiv preprint arXiv:2308.12966},
  year={2023},
  url={https://doi.org/10.48550/arXiv.2308.12966}
}

```
TOPSIS-SANYAM-GOYAL-102297005 0.0.1
A Python package to find TOPSIS for multi-criteria decision analysis method
License: MIT
Keywords: topsis,UCS654,TIET,data,science,Prashant Singh Rana

# TOPSIS-Python

Submitted By: **Sanyam Goyal 102297005**

***

## What is TOPSIS

**Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)**, is a decision-making method used in multi-criteria decision analysis. It is a mathematical technique that helps in ranking and selecting the best alternative from a set of options based on their proximity to an ideal solution. Check out more information here:[wikipedia](https://en.wikipedia.org/wiki/TOPSIS).

<br>

## How to use this package:

TOPSIS-SANYAM_GOYAL-102297005  can be run as in the following example:


### In Command Prompt to run the code:
```
python topsis input_data.csv "1,1,1,1" "+,+,-,+" output_data.csv
```
<br>

## Sample dataset

The decision matrix (`a`) should be constructed with each row representing a ID, and each column representing a criterion like Features

ID | Feature1 | Feature2 | Feature3 | Feature4
---|----------|----------|----------|----------
1 | 2 | 5 | 8 | 3
2 | 3 | 6 | 9 | 4
3 | 5 | 8 | 2 | 7
4 | 6 | 9 | 3 | 8

<br>

## Output

```
ID,Feature1,Feature2,Feature3,Feature4,Topsis Score,Rank
1,2,5,8,3,0.33629008441513597,3
2,3,6,9,4,0.26542732311540135,4
3,5,8,2,7,0.7345726768845987,1
4,6,9,3,8,0.6637099155848639,2

```
<br>
The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
pycounts-merete 0.1.1
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9

# pycounts_merete

Calculate word counts in a text file!


## Authors
Merete Lutz

## Installation

```bash
$ pip install pycounts_merete
```

## Usage

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

```python
from pycounts_merete.pycounts_merete import count_words
from pycounts_merete.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
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_merete` was created by Merete Lutz. It is licensed under the terms of the MIT license.

## Credits

`pycounts_merete` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter). `pycounts_merete` was created following the tutorial created by Tomas Beuzen, licensed under the terms
of the MIT license. A link to the tutorial can be found [here](https://py-pkgs.org/03-how-to-package-a-python#put-your-package-under-version-control)
pycounts-mjhz 0.1.1
Calculate word counts in a text file! A toy python package made for DSCI 524
License: MIT
Requires Python: >=3.9,<4.0

# pycounts

## Author: Mona Zhu

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_mjhz
```

## Usage

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

```python
from pycounts_mjhz.pycounts import count_words
from pycounts_mjhz.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
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_mjhz` was created by Tomas Beuzen. It is licensed under the terms
of the MIT license.

## Credits

`pycounts_mjhz` was created with 
[`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and 
the `py-pkgs-cookiecutter` 
[template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-sho-i98 0.1.1
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9

# pycounts_sho_i98

Calculate word counts in a text file!
Author

## Installation

```bash
$ pip install pycounts_sho_i98
```

## Usage

`pycounts_sho_i98` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_sho_i98.pycounts_sho_i98 import count_words
from pycounts_sho_i98.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
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_sho_i98` was created by Sho Inagaki. It is licensed under the terms of the MIT license.

## Credits

`pycounts_sho_i98` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-jy2024 0.2.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9

# pycounts_jy2024

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_jy2024
```

## Usage

`pycounts_jy2024` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_jy2024.pycounts_jy2024 import count_words
from pycounts_jy2024.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
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_jy2024` was created by Jerry Yu. It is licensed under the terms of the MIT license.

## Credits

`pycounts_jy2024` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-sandy 0.2.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9

# pycounts_sandy

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_sandy
```

## Usage

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

```python
from pycounts_sandy.pycounts_sandy import count_words
from pycounts_sandy.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
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_sandy` was created by Tomas Beuzen. It is licensed under the terms
of the MIT license.

## Credits

`pycounts_sandy` was created with 
[`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and 
the `py-pkgs-cookiecutter` 
[template](https://github.com/py-pkgs/py-pkgs-cookiecutter).