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Derek Tam's Projects

big-bench icon big-bench

Beyond the Imitation Game collaborative benchmark for enormous language models

big-bench-hard icon big-bench-hard

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

clip icon clip

Contrastive Language-Image Pretraining

continual-learning icon continual-learning

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, DGR, DGR+distill, RtF, iCaRL).

curvlinops icon curvlinops

scipy linear operators for the Hessian, Fisher/GGN, and more in PyTorch

factcc icon factcc

Resources for the "Evaluating the Factual Consistency of Abstractive Text Summarization" paper

fairseq icon fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

frank icon frank

FRANK: Factuality Evaluation Benchmark

git-theta icon git-theta

git extension for {collaborative, communal, continual} model development

mend icon mend

MEND: Fast Model Editing at Scale

mfma icon mfma

Factual consistency checking model for abstractive summaries (NAACL-22 Findings)

neural_wfst icon neural_wfst

Code for the paper 'Weighting Finite State Transductions with Neural Context', Pushpendre Rastogi, Ryan Cotterell, Jason Eisner

pet icon pet

This repository contains the code for "Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference"

promptsource icon promptsource

Toolkit for creating, sharing and using natural language prompts.

soft_patterns icon soft_patterns

Text classification code described in "SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines" by Roy Schwartz, Sam Thomson and Noah A. Smith, ACL 2018

summeval icon summeval

Resources for the "SummEval: Re-evaluating Summarization Evaluation" paper

swa_gaussian icon swa_gaussian

Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

t-few icon t-few

Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

uda icon uda

Unsupervised Data Augmentation (UDA)

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