- The fifth line applies a translation to the bunny mesh using the translate function. The translation vector used in this case is [2.5, 2.1, 1.2], which moves the bunny mesh 2.5 units along the x-axis, 2.1 units along the y-axis, and 1.2 units along the z-axis. Concept Here are ...
Using the natural language to Bash command (NL2SH) translation capabilities of large language models (LLMs) for command composition circumvents these issues. However, the NL2SH performance of LLMs is difficult to assess due to inaccurate test data and unreliable heuristics for determining the ...
在16B参数的StarCoder模型上,与其他指令调优模型进行基准测试,该方法在HumanEval Python基准上取得了最佳性能(46.2% pass@1)。 4.Mftcoder: Boosting code llms with multitask fine-tuning 5.Compilable neural code generation with compiler feedback 6.Coderl: Mastering code generation through pretrained models ...
StarCoder2, built byBigCodein collaboration with NVIDIA, is the most advanced code LLM for developers. You can build applications quickly using the model’s capabilities, including code completion, auto-fill, advanced code summarization, and relevant code snippet retrievals using natural language. The...
[全网首发中文版]LLM4Decompile: Decompiling Binary Code with Large Language Models,反编译是将已编译的机器代码或字节码转换回高级编程语言的过程。当源代码无法访问时,通常会这样做来分析软件的工作原理Brumley等人(2013);Katz等人(2018);胡赛尼和多兰-加维特(2022)
Human-LLM Interaction Datasets 8.1 Pretraining 8.2 Benchmarks Integrated Benchmarks Evaluation Metrics Program Synthesis Visually Grounded Program Synthesis Code Reasoning and QA Text-to-SQL Code Translation Program Repair Code Summarization Defect/Vulnerability Detection Code Retrieval Type Inference Commit ...
Code Translation Code LLMs are adept at translating code from one programming language to another, a task in which GPT-4 performs better. This capability facilitates code reuse across different technology stacks and simplifies the migration of legacy code. ...
本文首发于公众号:Angora热门前沿论文速递 , 关注每天推送最新研究进展~1. Code Llama:开源代码基础大模型 标题:Code Llama: Open Foundation Models for Code 相关领域:模型结构改进、预训练、指令微调、奖励…
Fine-Tuning Your Own Models: We provide an API for quickly fine-tuning your own LLMs for code using SOTA techniques forparameter-efficient fine-tuning(HuggingFace PEFT) on distributed environments. Supported Tasks: nl2code, code summarization, code completion, code translation, code refinement, clone...
LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing. - ghimiresunil/LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing