wentropy's repositories
Atlas-Of-Thrones
An interactive "Game of Thrones" map powered by Leaflet, PostGIS, and Redis.
Binary-Neural-Network-Keras
A Keras code on Binary Neural Networks
Binder
Code for the paper "Binding Language Models in Symbolic Languages"
caddy-docker-proxy
Caddy as a reverse proxy for Docker
Deep-Learning-A-Visual-Approach
All of the figures and notebooks for my deep learning book, for free!
Deep_Hierarchical_Classification
PyTorch Implementation of Deep Hierarchical Classification for Category Prediction in E-commerce System
deit-tf
Includes PyTorch -> Keras model porting code for DeiT models with fine-tuning and inference notebooks.
Diffusion-LM
Diffusion-LM
examples
Jina examples and demos to help you get started
information-retrieval
Neural information retrieval / semantic-search / Bi-Encoders
jina
Cloud-native neural search framework for ๐๐ฃ๐ฎ kind of data
Leaflet.MarkerPreCluster
Change the behavior of the MarkerCluster plugin to use data pre-clustered.
NLP-News-Scraping-Summarization-Sentiment
Using transformers to summarize and text classify news articles.
optimization-demo-files
Examples on numerical optimization
Question-Generation-Paper-List
A summary of must-read papers for Neural Question Generation (NQG)
rocket.chat-caddy
rocket.chat and caddy as reverse proxy with docker engine
rrkd
Official code for Relative Representation Knowledge Distillation (CORES 2023)
snorkel-tutorials
A collection of tutorials for Snorkel
tango
Codes and Model of the paper "Text-to-Audio Generation using Instruction Tuned LLM and Latent Diffusion Model"
textual
Textual is a TUI (Text User Interface) framework for Python inspired by modern web development.
Transformers-for-Natural-Language-Processing
Transformers for Natural Language Processing, published by Packt
transformersNLP
Jupyter notebooks for the Natural Language Processing with Transformers book
TransformerX
Flexible building blocks for Transformers (for tensorflow โ , pytorch ๐, and jax ๐)
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.