| Name | textforge JSON |
| Version |
0.1.2
JSON |
| download |
| home_page | None |
| Summary | Automated Synthetic Data Generation, Distillation, Quantization and Deployment Pipeline. |
| upload_time | 2025-03-04 02:26:06 |
| maintainer | None |
| docs_url | None |
| author | ameen-91 |
| requires_python | <4.0,>=3.11 |
| license | MIT |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# Infero
[](https://github.com/norsulabs/textforge/actions/workflows/ci.yaml)
## Overview
TextForge automates model distillation, training, quantization, and deployment for text classification. It simplifies synthetic data generation, model optimization using ONNX runtime, and FastAPI serving.
### Features
- Automated synthetic data generation
- Transformer model training
- ONNX conversion with 8-bit quantization
- Automated model API serving with FastAPI
<!-- - Customizable hyperparameter control -->
### Installation
```bash
pip install textforge
```
## Usage
```python
import pandas as pd
from textforge.pipeline import Pipeline, PipelineConfig
pipeline_config = PipelineConfig(
api_key=api_key,
labels=['business','education','entertainment','sports','technology'],
query="Classify based on headlines",
save_steps=200,
eval_steps=200,
epochs=10
)
df = pd.read_csv('data.csv')
pipeline = Pipeline(pipeline_config)
pipeline.run(data=df, save=True, serve=True)
```
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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"description": "# Infero\n\n\n\n\n[](https://github.com/norsulabs/textforge/actions/workflows/ci.yaml)\n\n\n## Overview\n\nTextForge automates model distillation, training, quantization, and deployment for text classification. It simplifies synthetic data generation, model optimization using ONNX runtime, and FastAPI serving.\n\n### Features\n\n- Automated synthetic data generation\n- Transformer model training\n- ONNX conversion with 8-bit quantization\n- Automated model API serving with FastAPI\n<!-- - Customizable hyperparameter control -->\n\n### Installation\n\n```bash\npip install textforge\n```\n\n## Usage\n\n```python\nimport pandas as pd\nfrom textforge.pipeline import Pipeline, PipelineConfig\n\npipeline_config = PipelineConfig(\n api_key=api_key,\n labels=['business','education','entertainment','sports','technology'],\n query=\"Classify based on headlines\",\n save_steps=200,\n eval_steps=200,\n epochs=10\n)\n\ndf = pd.read_csv('data.csv')\n\npipeline = Pipeline(pipeline_config)\n\npipeline.run(data=df, save=True, serve=True)\n```\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n",
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