semvec/pypi-packages huggingface dataset:
ohara 0.1.3
A collection of implementations of LLM, papers, and other models.
Requires Python: >=3.6

# Ohara

This is my collection of implimention of llm,paper and things I hand in my mind
I hand lot of fragmented code of implimention of diffrent model 

this is attempt to make it eveything in one place <br>
This lib is for runing/copying code for expriments
<br>
install with
```bash
git clone https://github.com/joey00072/ohara.git
pip install -e .
```
then

```bash
## download and pretokenize
python examples/prepare-dataset.py

## train 
## look at train.py its fairly easy
python examples/train_llama.py

# lighting fabric verison is also avalible (recommanded)
python examples/train_llama_fabric.py 
```
![alt text](./docs/src/image.png)

llama-20M trained on tinystores for 1.7B

inferance on phi2
```zsh
## this will download model from hf and run it in torch.flaot16

python phi_inference.py 

## look at files and you can impliment rest of things easily, 
## I belive in you 😉
```


###  The lib to maximize FAFO
papaers and theory is on one side but `code is truth`, in the end things that matter that works (runs)<br>
If you look into [docs](./docs/) you can find some written things. this are mostly copied from my obsidian notes


### WORK IS PROGESS (always)

### papers
1. [SwiGLU](./ohara/models/mlp.py) | [md](./docs/glu/GLU%20Variants%20Improve%20Transformer.md)
2. [Alibi Embeddings](./ohara/embedings_pos/alibi.py) | [md](./ohara/embedings_pos/alibi/alibi.md)
3. [Rotary Embeddings](./ohara/embedings_pos/rotatry.py) | [md](./docs/RoFormer.md) 
4. [LoRA ](./ohara/adaptor/lora.py)
5. [LLAMA](./ohara/llama/llama.py) | [md](./docs/llama/llama.md)
6. [XPOS](./ohara/embedings_pos/xpos.py)
7. [GPT](./ohara/models/gpt.py) | [md](./docs/gpt/gpt.md)
8. [Mamba](./ohara/models/mamba.py)
9. [renet](./ohara/models/retnet.py)


### More things are not in this repo
1. [TinyLora](https://github.com/joey00072/TinyLora)
2. [Neural Style Transfer in Pytorch](https://github.com/joey00072/Neural-Style-Transfer-in-Pytorch)



## TODO  (A lot)
- [ ] make infercer class better
- [ ] make training loop better (use lightning fabric maybe)
- [ ] Finetuning in structed way (I just rawdoag code when I need it)
- [ ] DPO 
- [ ] make is py modele so I can create expriment folder and put all this in it

## Fund My Caffeine Addiction 
[![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/R6R8KQTZ5)


### contribution guidelines
- be nice, 
- code explaintions || docs are appricated
- memes on pr recommend
time-until 0.1.3
Application that calculate time duration until reach a given date
Requires Python: >=3.10.15

# time-until-cli
> Application that calculate time duration until reach a given date.

**Main objective**: Understanding the logic of _Python_ app publishing and documenting it on a simple project.

## Usage

```bash
time_until 22h
```

## Application flow & use cases

Using CLI to calculate time duration to a given input date or timestamp. 

| Input | Output / Response |
| :---- | :---------------- |
| `time-until 23h` | Time remaining: 8 hour(s) 22 minute(s) 42 second(s) |
| `time-until 2023-02-27` | Time remaining: 04 month(s) 14 day(s) 8 hour(s) 22 minute(s) 42 second(s)  |

![app-flow-example](assets/time_until_app.png)

## Main goals

Build a Python app that works as a CLI (Command-line Interface) that receives a future date or time and returns a calculation of remaining time from now until that given date or time.

Once working, this project must be configured and submitted as Python package thru PyPI Modules. The process of development, build, release and publishing is the core of the project, to understand it and provice ideas and thoghts of process automation.

Feel free to initiate a discusison, open a issue or a pull request to this project. All kinds of contributions and ideas are welcome. **_Let's code!_**

## Development

A quick guide to contribute (or develop) on this project.

We recommend to [use an isolated environment](https://packaging.python.org/pt-br/latest/guides/installing-using-pip-and-virtual-environments/), then install the devolpment dependencies:

```bash
# For Unix / macOS systems

cd path/to/time-until # substitute with the real path to this project directory

# Activate Python enviroment
python3 -m venv .venv
source .venv/bin/activate

# Install development dependencies
pip install -r requirements-development.txt 
```

### Testing

With development dependencies installed, you can execute tests with *pytest*:

```bash
# Run tests
pytest
```

### Packaging

Create a package of this project with `wheel`:

```bash
# Build
python3 -m build --wheel
```
mucsi96.publish-tools 41.0.0
Publishing tools for continuous integration

# publish-tools
Tools for package publishing

# Maven

https://central.sonatype.com/

# GPG

https://central.sonatype.org/publish/requirements/gpg/#listing-keys

1. Install GNU GPG

```bash
brew install gnupg
```

2. Generate GPG keys

```bash
gpg --generate-key
```

3. Get key id

```bash
gpg --list-secret-keys --keyid-format=long
```

4. Export the gpg private key

```bash
gpg --export-secret-keys -a <key-id> > secret.txt
```

5. Distribute Your Public Key

```bash
gpg --keyserver keyserver.ubuntu.com --send-keys <your-key-id>
```
MikePrueba 0.1.0
Prueba para aprender a subir librerías a Pypi
Requires Python: >=3.6


# Mikel_Prueba

Este cÃ³digo es para practicar a subir archivos a Pypi.org para nuestra clase de programaciÃ³n.
EstÃ¡ en una versiÃ³n muy temprana como para meter mucho condicional.

# Comandos
- minusculas
    - Coge la frase y devuelve la frase en minÃºsculas (que innovador)
- mayusculas
    - Coge la frase y devuelve la frase en mayÃºsculas (guau, que increible)
- minusculas_en_frase
    - Coge la frase y devuelve una lista con las letras minÃºsculas Ãºnicas que haya en la frase 
- mayusculas_en_frase
    - Coge la frase y devuelve una lista con las letras mayÃºsculas Ãºnicas que haya en la frase 
- sumar
    - Coge una lista de nÃºmeros y suma los valores (guau)
- media
    - Coge una lista de nÃºmeros y calcula la media (por dios, que complejo)
- zeros
    - Coge una lista de nÃºmeros y cuenta cuÃ¡ntos ceros hay (yeahh)
- tipo
    - Coge la variable y dice su clase de variable (magistral, de alto nivel)
- varianza
    - Coge una lista de valores numÃ©ricos y calcula la varianza
- desviacion_estandar
    - Coge una lista de valores numÃ©ricos y calcula la desviaciÃ³n estandar.
## Authors

- Mikel Puerta
ugTranslate 0.2
A simple wrapper for translating text using Google Translate API
Requires Python: >=3.6

# ugTranslate

`ugTranslate` is a simple Python wrapper for translating text using the Google Translate API.
Translate without getting blocked!

# Installation

``
pip install ugTranslate
``

# Usage
``````
python

from ugTranslate import translate_text

# Translate text from English to Spanish

response = translate_text("Hello, world!", input_lang='en', output_lang='es')
print(response)
Mikel-Prueba 0.1.0
Prueba para aprender a subir librerías a Pypi
Requires Python: >=3.6


# Mikel_Prueba

Este cÃ³digo es para practicar a subir archivos a Pypi.org para nuestra clase de programaciÃ³n.
EstÃ¡ en una versiÃ³n muy temprana como para meter mucho condicional.

# Comandos
- minusculas
    - Coge la frase y devuelve la frase en minÃºsculas (que innovador)
- mayusculas
    - Coge la frase y devuelve la frase en mayÃºsculas (guau, que increible)
- minusculas_en_frase
    - Coge la frase y devuelve una lista con las letras minÃºsculas Ãºnicas que haya en la frase 
- mayusculas_en_frase
    - Coge la frase y devuelve una lista con las letras mayÃºsculas Ãºnicas que haya en la frase 
- sumar
    - Coge una lista de nÃºmeros y suma los valores (guau)
- media
    - Coge una lista de nÃºmeros y calcula la media (por dios, que complejo)
- zeros
    - Coge una lista de nÃºmeros y cuenta cuÃ¡ntos ceros hay (yeahh)
- tipo
    - Coge la variable y dice su clase de variable (magistral, de alto nivel)
- varianza
    - Coge una lista de valores numÃ©ricos y calcula la varianza
- desviacion_estandar
    - Coge una lista de valores numÃ©ricos y calcula la desviaciÃ³n estandar.
## Authors

- Mikel Puerta
dvrpsim 1.0.0
A package for modeling and simulating dynamic vehicle routing problems
Requires Python: >=3.8

# A Python package for dynamic vehicle routing

`dvrpsim` is a Python package for simulating dynamic vehicle routing problems (DVRPs).
This package provides a flexible and modular simulation environment that allows users to model a wide range of dynamic vehicle routing scenarios, with the ability to connect external routing algorithms implemented in any programming language.

For more details, check out the introduction, tutorial, and case studies!

## Installation

The package `dvrpsim` requires Python 3.8 or newer.
Since the package is included in the Python Package Index, once you have a Python installation, installing it is as simple as typing it at the command prompt:

```
python -m pip install dvrpsim
```
connectdev 0.1.0
Command-line tool for ConnectDev which is a platform that lets you host backends for your AI applications.
Requires Python: >=3.6

Command-line tool for ConnectDev.



# Install

```bash
pip install connectdev
```

# About ConnectDev

[ConnectDev](https://connectdev.io)  is a platform that lets you host backends for your applications. If you have web apps or backend programs built with Node.js, Python, Golang, you can deploy them to ConnectDev and it will automatically build runnable versions from the source code and run them in independent containers.

You can use this command-line tool to manage your applications on [ConnectDev](https://connectdev.io) , including creating, deploying.

If you are interested in [ConnectDev](https://connectdev.io) , please visit [website](https://connectdev.io) for more information. 

# Resources

Helpful links:
- [ConnectDev Website](https://connectdev.io)
- [ConnectDev Documentation](https://docs.connectdev.io)
- [Support Email](mailto:support@connectdev.io)
kal 0.6.0
Personal assistant cli tool
Requires Python: <4.0,>=3.11

# kal
kal은 개인용 어시스턴트 CLI 툴입니다.

개인 사용 목적으로 제작되어있기에 컨트리뷰트는 일절 받지 않습니다.


## Installation

```shell script
pip install kal
```