Papers with Code 아카이브

Code Generation

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하위 태스크: 5
평가표: 28
보존된 평가 기록: 241

Code Generation is an important field to predict explicit code or program structure from multimodal data sources such as incomplete code, programs in another programming language, natural language descriptions or execution examples. Code Generation tools can assist the development of automatic programming tools to improve programming productivity.

Source: Deep Learning for Source Code Modeling and Generation

Image source: Measuring Coding Challenge Competence With APPS

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ganjinzero/rrhf

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

https://github.com/gen-verse/reasonflux

Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

https://github.com/ggerganov/llama.cpp

LLaMA: Open and Efficient Foundation Language Models

https://github.com/ggml-org/llama.cpp

LLaMA: Open and Efficient Foundation Language Models

https://github.com/glb400/Toy-RecLM

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://github.com/glouppe/info8010-deep-learning

Evaluating Large Language Models Trained on Code

https://github.com/google-deepmind/code_contests

Competition-Level Code Generation with AlphaCode

https://github.com/google/paxml

PaLM: Scaling Language Modeling with Pathways

https://github.com/google/t5patches

Controlling Conditional Language Models without Catastrophic Forgetting

https://github.com/gpt4life/alpagasus

GPT-4 Technical Report

https://github.com/grantslatton/llama.cpp

LLaMA: Open and Efficient Foundation Language Models

https://github.com/graykode/commit-autosuggestions

CodeBERT: A Pre-Trained Model for Programming and Natural Languages

https://github.com/greenbitai/low_bit_llama

LLaMA: Open and Efficient Foundation Language Models

https://github.com/gsh2014/grammar-coarse2fine

A Syntactic Neural Model for General-Purpose Code Generation

https://github.com/guinmoon/llmfarm

LLaMA: Open and Efficient Foundation Language Models

https://github.com/guppykang/joshFaceV2

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

https://github.com/gurushantj/MTCNN

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

https://github.com/hamidriasat/AlphaCodium

Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering

https://github.com/hamishivi/easylm

LLaMA: Open and Efficient Foundation Language Models

https://github.com/haoyuhsu/autovfx

AutoVFX: Physically Realistic Video Editing from Natural Language Instructions

https://github.com/hit-scir/chinese-mixtral-8x7b

Mixtral of Experts

https://github.com/holarissun/rewardmodelingbeyondbradleyterry

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs

https://github.com/huawei-noah/noah-research/tree/master/NLP/DA4CodeGeneration

Exploring Data Augmentation for Code Generation Tasks

https://github.com/huggingface/transformers

LLaMA: Open and Efficient Foundation Language Models

https://github.com/ibm/data-prep-kit

Granite Code Models: A Family of Open Foundation Models for Code Intelligence

https://github.com/icalk-nlp/educhat

LLaMA: Open and Efficient Foundation Language Models

https://github.com/icey-zhang/MTCNN_paddle

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

https://github.com/idiap/abroad-re

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://github.com/iitmcvg/Demo-of-face-detection-and-counting-

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

https://github.com/iml130/nncg

A C Code Generator for Fast Inference and Simple Deployment of Convolutional Neural Networks on Resource Constrained Systems

https://github.com/ist-daslab/rosa

Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

https://github.com/jetbrains-research/commit_message_generation

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

https://github.com/jimmy0087/faceai-master

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

https://github.com/jingyaogong/minimind

Mixtral of Experts

https://github.com/jmbuba/llm-semantic-perf

Clover: Closed-Loop Verifiable Code Generation

https://github.com/jmysu/ESP32CAM-FaceDetect-Line-Notify

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.