semvec/pypi-packages huggingface dataset:
hoogberta 0.1.1
HoogBERTa: Multi-task Sequence Labeling using Thai Pretrained Language Representation
License: MIT
Keywords: HoogBERTa: Multi-task Sequence Labeling using Thai Pretrained Language Representation

# HoogBERTa

This repository includes the Thai pretrained language representation (HoogBERTa_base) and the fine-tuned model for multitask sequence labeling.

# Installation

```
$ python setup.py install
```

To download model, use

```
>>> import hoogberta
>>> hoogberta.download() # or hoogberta.download('/home/user/.hoogberta/')
```

# Usage

see test.py


# Documentation

To annotate POS, NE and cluase boundary, use the following commands

```python
from hoogberta.multitagger import HoogBERTaMuliTaskTagger
tagger = HoogBERTaMuliTaskTagger(cuda=False) # or cuda=True
output = tagger.nlp("วันที่ 12 มีนาคมนี้ ฉันจะไปเที่ยววัดพระแก้ว ที่กรุงเทพ")
```

Please give the "base path" parameter if you have changed the "models" directory to a different location than the current one, for example. 

```python
tagger = HoogBERTaMuliTaskTagger(cuda=False,base_path="/home/user/.hoogberta/" ) 
```

The output is a list of annotations (token, POS, NE, MARK). "MARK" is annotation for a single white space that can be PUNC (not clause boundary) or MARK (clause boundary). Note that, for clause boundary classification, the current pretrained model works well with inputs containing two clauses. If you want a more precise result, we recommend running tagger.nlp iteratively.

To extract token features, based on the RoBERTa architecture, use the following commands

```python
from hoogberta.encoder import HoogBERTaEncoder
encoder = HoogBERTaEncoder(cuda=False) # or cuda=True
token_ids, features = encoder.extract_features("วันที่ 12 มีนาคมนี้ ฉันจะไปเที่ยววัดพระแก้ว ที่กรุงเทพ")
```

For batch processing,

```python
inputText = ["วันที่ 12 มีนาคมนี้","ฉันจะไปเที่ยววัดพระแก้ว ที่กรุงเทพ"]
token_ids, features = encoder.extract_features_batch(inputText)
```

To use HoogBERTa as an embedding layer, use

```python
tokens, features = encoder.extract_features_from_tensor(token_ids) # where token_ids is a tensor with type "long".
```

# Citation

Please cite as:

``` bibtex
@inproceedings{porkaew2021hoogberta,
  title = {HoogBERTa: Multi-task Sequence Labeling using Thai Pretrained Language Representation},
  author = {Peerachet Porkaew, Prachya Boonkwan and Thepchai Supnithi},
  booktitle = {The Joint International Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP 2021)},
  year = {2021},
  address={Online}
}
```

Download full-text [PDF](https://drive.google.com/file/d/1jXYscGOeUASBJI9cMfj2sAzthEFPp9Gr/view?usp=sharing)
tess-atlas 0.0.3a0
All the TESS exoplanets!
License: MIT

[![Unit 🧪 `template.ipynb`](https://github.com/dfm/tess-atlas/workflows/Unit%20%F0%9F%A7%AA%20%60template.ipynb%60/badge.svg)](https://github.com/dfm/tess-atlas/actions?query=workflow%3A%22Unit+%F0%9F%A7%AA+%60template.ipynb%60%22)
[![end-to-end 🧪 `template.ipynb`](https://github.com/dfm/tess-atlas/workflows/end-to-end%20%F0%9F%A7%AA%20%60template.ipynb%60/badge.svg)](https://github.com/dfm/tess-atlas/actions?query=workflow%3A%22end-to-end+%F0%9F%A7%AA+%60template.ipynb%60%22)
[![](https://img.shields.io/badge/Paper-Download-orange)](https://nightly.link/dfm/tess-atlas/workflows/build_paper/paper/main.pdf.zip)

<p align="center">
  <img width = "450" src="docs/_static/atlas_logo.png" />
  <br>
  <b>TESS Atlas</b>
</p>

## Installation instructions
To install the necessary packages, run
```bash
python -m pip install -e .
```

## Instructions to update TESS Atlas
1. Create and analyse some TOIs with the following: `make run`
2. Commit the completed TOIs to a branch and make a PR to main
3. Once PR to main completed, run `make website` to convert the notebooks to HTML and upload to the gh-pages branch and deploy to github-pages

## How to use
To run the analysis for one TOI, you can run
```bash
run_toi <toi id number>
```
where an example `<toi id number> = 724`

To only setup the notebook + data needed for the analysis for one TOI, you can run
```bash
run_toi <toi id number> --setup
```
where an example `<toi id number> = 724`

To run all the notebooks (in batches of 8), you can run
```bash
run_tois
```

To make the slurm files needed to analyse a CSV of TOIs you can run:
```bash
make_slurm_job --toi_csv toi_ids.csv --module_loads "git/2.18.0 gcc/9.2.0 openmpi/4.0.2 python/3.8.5"
```

## Run tests on template.ipynb
```bash
python -m pip install -e ".[test]"
pytest tests/
```
manim-editor 0.3.8
Editor and Presenter for Manim Generated Content.
License: MIT
Requires Python: >=3.7,<4.0

<p align="center">
    <a href="#"><img src="https://raw.githubusercontent.com/ManimCommunity/manim_editor/main/manim_editor/app/static/img/banner.png"></a>
    <br />
    <br />
    <a href="https://pypi.org/project/manim-editor/"><img src="https://img.shields.io/pypi/v/manim-editor.svg?style=flat&logo=pypi" alt="PyPI Latest Release"></a>
    <a href="https://docs.editor.manim.community/en/stable/"><img src='https://readthedocs.org/projects/manim-editor/badge/?version=stable' alt='Documentation Status' /></a>
    <a href="http://choosealicense.com/licenses/mit/"><img src="https://img.shields.io/badge/license-MIT-red.svg?style=flat" alt="MIT License"></a>
    <a href="https://github.com/ManimCommunity/manim_editor/actions/workflows/build_pages.yml"><img src="https://github.com/ManimCommunity/manim_editor/actions/workflows/build_pages.yml/badge.svg" alt="MIT License"></a>
    <br />
    <br />
    <i>Editor and Presenter for Manim Generated Content.</i>
</p>
<hr />

Take a look at the [Working Example](https://ManimCommunity.github.io/manim_editor/).
More information can be found in the [documentation](https://docs.editor.manim.community/en/stable/).

These Browsers are supported:
- Firefox
- Chrome/Chromium-Based
- Edge

## Create a Project

![create_project](https://raw.githubusercontent.com/ManimCommunity/manim_editor/main/docs/source/_static/create_project.gif)

## Export a Project as a Presentation

![export_presenter](https://raw.githubusercontent.com/ManimCommunity/manim_editor/main/docs/source/_static/export_presenter.gif)