Top Results for Research Model

Cupiennius salei, commonly known as a type of wandering spider, is a large arachnid belonging to the family Ctenidae. It was first described by Friedrich Wilhelm Keyserling in 1877 and is native to the tropical forests of Central America. The species is nocturnal, relying on tactile and vibration cu...

OLMo 2 is a fully open-source large language model developed by the Allen Institute for AI (AI2) and released in 2024. As the second generation of the OLMo project, it provides the research community with open access to model weights, training datasets, intermediate checkpoints, and training code. T...

DeepBach is an AI research project exploring musical generation. It utilizes a recurrent neural network to create new chorales in the style of Johann Sebastian Bach. Trained on Bach's existing works, the system produces compositions resembling his past style. Researchers and musicologists studying B...

Pythia is a suite of 16 open-source language models developed by EleutherAI in 2023, ranging from 70 million to 12 billion parameters. The models were trained on identical data sequences with publicly available checkpoints at regular intervals, specifically designed to enable scientific study of lar...

Alpaca is an instruction-following language model released by Stanford researchers in March 2023. It was fine-tuned from Meta's LLaMA 7B model using 52,000 instruction-response examples generated with OpenAI's text-davinci-003 model through a self-instruct process. The project demonstrated that a re...

OLMo, or Open Language Model, is a series of artificial intelligence models released by the Allen Institute for AI (AI2) in 2024. It distinguishes itself from many contemporary models by offering a fully transparent open-source framework, which includes the complete training code, the pre-training d...

MiniGPT-4 is a vision-language model introduced in 2023 by researchers at King Abdullah University of Science and Technology (KAUST). It aligns a frozen visual encoder derived from BLIP-2 with a frozen Vicuna large language model using a single linear projection layer trained on a comparatively smal...

BertSum is a neural network summarization approach utilizing pre-trained BERT embeddings to generate abstractive summaries of input texts, often prioritizing semantic understanding over direct extraction.

The Brazilian short-tailed opossum, scientifically known as Monodelphis domestica, is a small marsupial native to the forests and savannas of Brazil, Bolivia, and Paraguay. Unlike many other marsupials, it lacks a true pouch, with newborn young attaching directly to the mother's teats for early deve...

OpenCoder is an extension for Microsoft Copilot that utilizes OpenAI’s Codex models to generate code snippets and complete functions based on natural language prompts, primarily focused on Python development within the Visual Studio Code environment.

MAP-Neo is a bilingual large language model developed by the OpenBMB team and researchers from the University of Science and Technology of China (USTC), released in 2024. It is designed as a fully open-source project, providing open access to its code, model weights, and training datasets. The model...

CTRLsum is a neural text summarization model developed by Salesforce Research that allows for the controllable generation of document summaries. Unlike standard unsupervised summarizers, it enables users to guide the output by providing specific keywords, length constraints, or structural preference...

SummaRuNNer is a recurrent neural network (RNN) model designed for extractive document summarization. Introduced in a 2017 paper by researchers at IBM, the model processes text at the sentence level to predict which sentences should be selected to form a concise summary. It operates by classifying e...

Magic is an open-source extension for AI chatbots like ChatGPT that allows users to execute Python code within the chat interface, enabling complex calculations and data analysis directly through conversational prompts.

PolyCoder is a large language model developed by Salesforce Research, trained on a massive dataset of code and designed to generate code in over 20 programming languages with improved multilingual capabilities.