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Forrest Bao (forrestbao)

forrestbao

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Company:Iowa State University

Location:Ames, IA

Home Page:forrestbao.github.io

Twitter:@forrestbao

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TexteaInc

Forrest Bao's repositories

Run

CS教授的靠譜潤學

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pyeeg

Python + EEG/MEG = PyEEG

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MLClass

Introduction to Machine Learning class taught at ISU, Fall 2020 to Spring 2021

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nlp-class

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autoscholar

A computer program that automatically reads scientific papers for you

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ChatPaper

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vectara-python-cli

An unofficial Python SDK and CLI for Vectara RAG platform

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covid-19

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forrestbao.github.io

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Rect_in_Poly

Pack rectangles into a polygon as many as possible

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SueNes

A weakly supervised summary quality metric (NAACL 2022 paper)

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verified_calibration

Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlight).

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AFFiNE

There can be more than Notion and Miro. AFFiNE is a next-gen knowledge base that brings planning, sorting and creating all together. Privacy first, open-source, customizable and ready to use.

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AgeML

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AppFlowy

AppFlowy is an open-source alternative to Notion. You are in charge of your data and customizations. Built with Flutter and Rust.

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codepod

Codepod IDE: Scalable Interactive Coding

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Funix-Ref

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funix_scipy_2024_proceedings

Funix paper for Scipy 2024

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hallucination-leaderboard

Leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents

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HappySearch

Searching in the transcript of a Youtube Video and jump to the matching timestamp

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HHEM-web-app

A web demo of HHEM-2.1-Open hallucination detection model.

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InterfacesForRanking

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json-viewer

not only a JSON viewer

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lit-gpt-bao

Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

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papers

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ProfKungFun

Prof. Kung Fun 孔方教授

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ReactFlowPlay

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RePublic

a demostrative public library of functions to be hosted by Redstone and XiPage

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summac

Codebase, data and models for the SummaC paper in TACL

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SyngasMachineLearning

An evaluation of machine learning algorithms in predicting Clostridium syngas fermentation outcomes with limited experimental data

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