Griffin Adams's repositories
calibrating-summaries
This is the official PyTorch codebase for the ACL 2023 paper: "What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization".
contrast-sum
Factual Summarization with Contrast Sets
abstract_gen
Chemical Abstract Generation
chemotaxis
Code for COMS 4444 Chemotaxis Project - Fall 2021
clinical-led-summarizer
HuggingFace Model Weights for the LongFormer Hospital-Course Summarization from "Learning to Revise References for Faithful Summarization"
coms4444_flowers
Columbia COMS 4444 (Fall 2021): Flower Arrangements, Project 3
griff4692.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
lit-parrot
Implementation of Falcon, StableLM, Pythia, INCITE language models based on nanoGPT. Supports flash attention, LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
nested_coref_resolver
Script to replace co-referent clusters with first non-pronominal mention
redress-clinical-hallucination-generator
HuggingFace model weights for Clinical Text Hallucination Generator
axolotl-bhc
Go ahead and axolotl questions
cold-compress
Cold Compress is a hackable, lightweight, and open-source toolkit for creating and benchmarking cache compression methods built on top of GPT-Fast, a simple, PyTorch-native generation codebase.
ctc-gen-eval
EMNLP 2021 - CTC: A Unified Framework for Evaluating Natural Language Generation
fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
frank-annotation-platform
Annotation Platform for FRANK
lm-evaluation-harness
A framework for few-shot evaluation of autoregressive language models.
progressive-qlora
QLoRA: Efficient Finetuning of Quantized LLMs
pycoms4444
TA codebase
question_generation
Neural question generation using transformers
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
TransformerSum
Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.