ishandutta2007

ishan dutta's repositories

lammps

Public development project of the LAMMPS MD software package

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cgal

The public CGAL repository, see the README below

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ChatGPT-Next-Web

One-Click to deploy well-designed ChatGPT web UI on Vercel. 一键拥有你自己的 ChatGPT 网页服务。

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notes for software engineers getting up to speed on new AI developments. Serves as datastore for https://latent.space writing, and product brainstorming, but has cleaned up canonical references under the /Resources folder.

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Auto-GPT

An experimental open-source attempt to make GPT-4 fully autonomous.

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awesome-angular

:page_facing_up: A curated list of awesome Angular 2 and Angular 4 resources by @AngularClass

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biopython

Official git repository for Biopython (originally converted from CVS)

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brave-browser

Next generation Brave browser for macOS, Windows, Linux, and eventually Android

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ChatALL

Concurrently chat with ChatGPT, Bing Chat, bard, Alpaca, Vincuna, Claude, ChatGLM, MOSS, iFlytek Spark, ERNIE and more, discover the best answers

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chatgpt-api

Node.js client for the official ChatGPT API. 🔥

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daily-api

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dlib

A toolkit for making real world machine learning and data analysis applications in C++

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graphql.github.io

GraphQL Documentation at graphql.org

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hugo-toha.github.io

An example hugo static site with Toha theme.

MIT100

hypre

Parallel solvers for sparse linear systems featuring multigrid methods.

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JARVIS

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf

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LocalAI

:robot: Self-hosted, community-driven, local OpenAI-compatible API. Can be used as a drop-in replacement for OpenAI, running on CPU with consumer-grade hardware. API for ggml compatible models, for instance: llama.cpp, alpaca.cpp, gpt4all.cpp, rwkv.cpp, whisper.cpp, vicuna, koala, gpt4all-j, cerebras

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opencv

Open Source Computer Vision Library

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ore_algebra

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pendulum

Python datetimes made easy

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RefPerSys

Reflexive & Persistent System (artificial intelligence)

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RWKV-LM

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

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