Sentence Completion

45 papers with code • 1 benchmarks • 2 datasets

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Libraries

Use these libraries to find Sentence Completion models and implementations

Most implemented papers

RoBERTa: A Robustly Optimized BERT Pretraining Approach

pytorch/fairseq 26 Jul 2019

Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging.

Language Models are Few-Shot Learners

openai/gpt-3 NeurIPS 2020

By contrast, humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do.

LLaMA: Open and Efficient Foundation Language Models

facebookresearch/llama arXiv 2023

We introduce LLaMA, a collection of foundation language models ranging from 7B to 65B parameters.

Llama 2: Open Foundation and Fine-Tuned Chat Models

facebookresearch/llama 18 Jul 2023

In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters.

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

state-spaces/mamba 1 Dec 2023

Foundation models, now powering most of the exciting applications in deep learning, are almost universally based on the Transformer architecture and its core attention module.

DeBERTa: Decoding-enhanced BERT with Disentangled Attention

microsoft/DeBERTa ICLR 2021

Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks.

GPT-4 Technical Report

openai/evals Preprint 2023

We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs.

Finetuned Language Models Are Zero-Shot Learners

google-research/flan ICLR 2022

We show that instruction tuning -- finetuning language models on a collection of tasks described via instructions -- substantially improves zero-shot performance on unseen tasks.

PaLM: Scaling Language Modeling with Pathways

lucidrains/CoCa-pytorch Google Research 2022

To further our understanding of the impact of scale on few-shot learning, we trained a 540-billion parameter, densely activated, Transformer language model, which we call Pathways Language Model PaLM.

Mistral 7B

mistralai/mistral-src 10 Oct 2023

We introduce Mistral 7B v0. 1, a 7-billion-parameter language model engineered for superior performance and efficiency.