Metadata-Version: 2.4
Name: dwl-cli
Version: 1.0.0
Summary: Command-line interface for fast model training
Home-page: https://zhuomingli000.github.io/dwlapp
Author: Eury AI Team
Author-email: zhuoming.li01@gmail.com
Keywords: deep-learning,machine-learning,nlp,transformers,training
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: requests>=2.25.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# DWL CLI Tool

Command-line interface for training DWL (Deep Weight Learning) models.

## Installation

```bash
pip install dwl-cli
```

## Usage

```bash
# Basic DWL training
dwl-train --model bert-base-uncased --dataset yahoo_answers_topics

# Traditional training with custom parameters
dwl-train --model roberta-base --dataset ag_news --method traditional --epochs 50 --lr 0.0001

# DWL training with custom components
dwl-train --model distilbert-base-uncased --dataset emotion --components 100 --epochs 30

# Non-verbose mode
dwl-train --model bert-base-uncased --dataset imdb --quiet

# Use custom backend URL
dwl-train --model bert-base-uncased --dataset ag_news

# List available options
dwl-train --list-models
dwl-train --list-datasets

# Get help
dwl-train --help
```

## Features

- **Easy to use**: Simple command-line interface
- **Flexible**: All training parameters configurable
- **Real-time streaming**: See training progress as it happens
- **Multiple models**: Support for BERT, RoBERTa, DistilBERT, and more
- **Multiple datasets**: 12+ text classification datasets
- **Remote support**: Can connect to any backend URL

## Available Models

- bert-base-uncased
- bert-large-uncased
- roberta-base
- roberta-large
- distilbert-base-uncased
- albert-base-v2
- xlnet-base-cased

## Available Datasets

- ag_news
- dbpedia_14
- yahoo_answers_topics
- yelp_review_full
- yelp_polarity
- amazon_polarity
- trec
- emotion
- go_emotions
- imdb
- banking77
- rotten_tomatoes

## License

MIT License
