Models, data loaders and abstractions for language processing, powered by PyTorch
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Updated
Sep 25, 2024 - Python
Models, data loaders and abstractions for language processing, powered by PyTorch
Basic Utilities for PyTorch Natural Language Processing (NLP)
Python library for handling audio datasets.
PyTorch DataLoader processed in multiple remote computation machines for heavy data processings
DaLI (Data Loader Interface) is a data loader and input generator for RP2 (https://pypi.org/project/rp2), the privacy-focused, free, open-source cryptocurrency tax calculator: DaLI removes the need to manually prepare RP2 input files. Just like RP2, DaLI is also free, open-source and it prioritizes user privacy.
PyTorch tutorial for computer vision
A tensorflow-based implementation of SISR using EDSR, SRResNet, and SRGAN
Training framework & tools for PyTorch-based machine learning projects.
A utility for wrapping the Free Spoken Digit Dataset into PyTorch-ready data set splits.
Implementation for Video Frame Interpolation Via Down-Up Scale Generative Adversarial Networks (2022).
A Python package to load complex XML files into a relational database
Versatile Data Ingestion Pipelines for Jax
Use PyTorch style dataloaders with other deep learning frameworks
Python service : insert data from a directory inside postgres db or inside elastic.
A Keras like Image Data Generator using TensorFlow's multithreading
`Spltr` is a simple PyTorch-based data loader and splitter. It may be used to load arrays and matrices or Pandas DataFrames and CSV files containing numerical data with subsequent split it into train, test (validation) subsets in the form of PyTorch DataLoader objects.
Universal-EDA: Simplify Exploratory Data Analysis with versatile data loading & analysis tools for various datasets & CSVs.
Small tool for aggregating and grouping data. Written in Python, mimicking functionality of my older C++ data-explorer project. Created to refresh Python skills, have some fun and compare speed of C++/Go/Python versions.
PyTorch Implementation of Spatially Consistent Representation Learning(SCRL)
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