semvec/pypi-packages huggingface dataset:
cosine-warmup 0.0.0
Cosine Annealing Linear Warmup
Requires Python: >=3.8
Keywords: torch,scheduler

# Cosine Annealing Scheduler with Linear Warmup

Implementation of a Cosine Annealing Scheduler with Linear Warmup and Restarts in PyTorch. \
It has support for multiple parameters groups and minimum target learning rates. \
Also works with the Lightning Modules!

# Installation

```pip install 'git+https://github.com/santurini/cosine-annealing-linear-warmup'```

# Usage

It is important to specify the parameters groups in the optimizer instantiation as the learning rates are directly inferred from the wrapped optimizer.

#### Example: Multiple groups

```
from cosine_warmup import CosineAnnealingLinearWarmup

optimizer = torch.optim.Adam([
    {"params": first_group_params, "lr": 1e-3},
    {"params": second_group_params, "lr": 1e-4},
    ]
)

scheduler = CosineAnnealingLinearWarmup(
    optimizer = optimizer,
    min_lrs = [ 1e-5, 1e-6 ],
    first_cycle_steps = 1000,
    warmup_steps = 500,
    gamma = 0.9
    )
    
# this is equivalent to

scheduler = CosineAnnealingLinearWarmup(
    optimizer = optimizer,
    min_lrs_pow = 2,
    first_cycle_steps = 1000,
    warmup_steps = 500,
    gamma = 0.9
    )
```

#### Example: Single groups

```
from cosine_linear_warmup import CosineAnnealingLinearWarmup

optimizer = torch.optim.Adam(model.parameters(), lr=1e-3)

scheduler = CosineAnnealingLinearWarmup(
    optimizer = optimizer,
    min_lrs = [ 1e-5 ],
    first_cycle_steps = 1000,
    warmup_steps = 500,
    gamma = 0.9
    )
    
# this is equivalent to

scheduler = CosineAnnealingLinearWarmup(
    optimizer = optimizer,
    min_lrs_pow = 2,
    first_cycle_steps = 1000,
    warmup_steps = 500,
    gamma = 0.9
    )
```

# Visual Example

![Unknown-2](https://user-images.githubusercontent.com/91251307/232208248-a1aa9546-39ff-4456-936a-4953a3cb0d27.png)
streamlit-text-annotator 0.1.4
Component for annotating text for NLP resolution
Requires Python: >=3.8

<h1> streamlit-annotation </h1>

- [Install](#install)
- [Quick Use](#quick-use)
- [Development](#development)
  - [Install](#install-1)
  - [Run](#run)
- [License](#license)
- [Author](#author)
- [Contributors](#contributors)


# Install

```
pip install streamlit-annotation
```

# Quick Use

Create an example.py file

```python
from st_text_annotator import StTextAnnotator

text = "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aenean et hendrerit orci. Praesent auctor malesuada lobortis. Suspendisse ac elit bibendum, congue tellus vel, ornare ipsum. Mauris at tellus in turpis aliquet cursus."

StTextAnnotator(text)
```

Run:

```
streamlit run example.py
```

# Development

## Install

```
git clone git@github.com:rmarquet21/streamlit-text-annotator.git
cd streamlit-text-annotator
pip install -e .
```

## Run

```
streamlit run example.py
```

# License

MIT

# Author

Robin Marquet

# Contributors

- [Robin Marquet](robin.marquet3@gmail.com)
e621-data 1.0.0
Load the e621 exported data
Requires Python: >=3.9

# E621-Data

Load the e621 export data in a python format lazily.

```python
from e621_data import load_posts

for post in load_posts("./posts-2023-04-14.csv"):
    print(post)
>>>

Post(
    id=491,
    uploader_id=7,
    created_at=datetime.datetime(2007, 2, 17, 10, 35, 32, 756555),
    updated_at=datetime.datetime(2023, 2, 19, 13, 26, 54, 614594),
    source='https://inkbunny.net/Arcturus',
    rating='s',
    tags=[
        '2005',
        '<3',
        'ambiguous_gender',
        'anthro',
        'arcturus_(n)',
        'blue_body',
        'clothed',
        'clothing',
        'crimson',
        'dragon',
        'duo',
        'exclamation_point',
        'eyewear',
        'garrett',
        'gloves',
        'handwear',
        'headphones',
        'inline_skates',
        'jet_set_radio',
        'lizardbeth',
        'male_(lore)',
        'red_body',
        'roller_skates',
        'scalie',
        'simple_background',
        'skating',
        'sunglasses',
        'thief',
        'thief_(series)',
        'upside_down'
    ],
    md5='dee7546d137a6df8bc67ca1c2205836c',
    file_ext='jpg',
    file_size=217339,
    image_width=675,
    image_height=883,
    locked_tags='',
    fav_count=15,
    parent_id=None,
    change_seq=42697063,
    approver_id=17633,
    comment_count=6,
    description='',
    duration=None,
    score=3,
    up_score=7,
    down_score=-4,
    is_deleted=False,
    is_pending=False,
    is_flagged=False,
    is_rating_locked=True,
    is_status_locked=False,
    is_note_locked=False
)
```

## Installation

[https://pypi.org/project/e621-data/](https://pypi.org/project/e621-data/)
```
python -m pip install e621-data
```
pyexhange-r3ne 0.1.9
Python code that allows users to create and manage their own virtual wallets to get the trading experiense with out real money.
Requires Python: >=3.7

# PyExhange

This code is a Python implementation of a basic wallet system that allows users to buy, sell, and transfer currencies. It includes a JSON database to store user information and currency balances. The code is licensed under the MIT license.

# Installation
```
pip install pyexhange-r3ne
```

# Usage
This can be integrated to any interface (Websites, Telegram, Discord, etc.) with ease.

Example:
```python
import pyexhange

#Buy 1 Ethereum
print(pyexhange.handle_command("trade 1 1 eth"))

#Sell 1 Ethereum
print(pyexhange.handle_command("trade 1 -1 eth"))

#As user 1 send 100 dollars to user 2
print(pyexhange.handle_command("send 1 2 100 USD This_Is_A_Message"))
```
xfaas-core-python3 0.0.5
XFaaS package for Python3
Requires Python: >=3.7

# Build the package

The build files are located in <code>./dist</code>.

- <code>python3 -m build</code>

# Upload the package to [PyPi](https://test.pypi.org/account/login/?next=%2Fmanage%2Faccount%2F)

- Install twine if necessary <code>python3 -m pip install --upgrade twine</code>
- <code>python3 -m twine upload --repository pypi dist/*</code>
- User <code>__token__</code> as username and token with <code>pypi-</code> prefix.

# Install the package

- <code>pip install xfaas_core_python3</code>