semvec/pypi-packages huggingface dataset:
pythings 0.1.2
A zero-depedencies and most-used python resources.
License: MIT

## pythings
A zero-depedencies and most-used python resources.

### Available resources
- Convertions
> More convertions can be added.

### Features
- Operations
- Web scrapping
- Convertions

### Usage
1. Use PyPi to install _pythings_ in your computer.
2. Open new terminal in your code enviroment and type below:
`pip install pythings`

### Writing our first program with _pythings_
```python
from pythings.convertions import Convertions

# Lets create an object
c = Convertions()

# Calling this convertion method
c.text_to_binary("foo")

# Output:
# 01100110 01101111 01101111
```
### License
MIT License - [Read full LICENSE](./LICENSE)
snapml-auto-quantization 0.0.8
A automatic pipeline for SnapML quantization
License: MIT
Requires Python: >=3.6

# SnapML Automatic Quantization Pipeline

## Installation:

    pip install git+ssh://git@github.sc-corp.net/Snapchat/snapml_auto_quantization.git --upgrade    

## Uninstallation:

    pip uninstall snapml_auto_quantization

## Exporting ONNX Models:

    torch.onnx.export(net, inputs, onnx_path, verbose=verbose,
                      input_names=input_names, output_names=output_names,
                      keep_initializers_as_inputs=True,
                      operator_export_type=
                      torch.onnx.OperatorExportTypes.ONNX_ATEN_FALLBACK,
                      opset_version=None)

## API Documenation

[Documentation](https://github.sc-corp.net/pages/Snapchat/snapml_auto_quantization/)