Arijit Sehanobish's Projects
Make a drawing app! Challenge for prospective apprentices.
Huggingface Transformers + Adapters = ❤️
An open-source NLP research library, built on PyTorch.
The Abstraction and Reasoning Corpus
Paper list for equivariant neural network
TensorFlow code and pre-trained models for BERT
Models that use BERT + Chinese Glyphs for NER
This is new BERT based model for OCR
Tool for visualizing attention in the Transformer model (BERT, GPT-2, XLNet, and RoBERTa)
Implementation of the conditionally routed attention in the CoLT5 architecture, in Pytorch
Repo for various contrastive losses
Cracking the Coding Interview 6th Ed. Python Solutions
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
This repository contains implementations and illustrative code to accompany DeepMind publications
Using set encoders to encode Wasserstein Spaces
Adaption of performers to enformer
The idea is to test "fairness". Start with 50 districts with two candidates running in each election. Suppose Party A wins 55% of the popular vote. We want to see how many seats does party A win. For this, we choose 50 random numbers between 0 and 1 as the proportion of people who voted for party A and then we simulate this a bunch of times and see the scatter plot.
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Repo for various RPE/Masking Mechanisms for low rank attention.
Algorithms for efficient graph field integration
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Understanding non-Euclidean latent spaces for representation learning
Computations and statistics on manifolds with geometric structures.
Glyce: Glyph-vectors for Chinese Character Representations
gpt4all: an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue
Variants of graphformer to node classification
TensorFlow implemenation of GRu4Rec model
Repo to store code for experiments with Hamiltonian Neural networks