如果要看sota大模型的代码评测榜单可以参考EvalPlus Leaderboard。 历来Sota工作 预训练Code LLM 预训练模型分为开源和闭源两块,闭源里面只有GPT4和GPT4o大家比较关注。开源里面在code领域较为关注的有LLama3系列,DeekSeek v2系列,DeekSeek Coder v2系列,Qwen2系列,Mistral系列。从目前各家预训练开放的技术报告来看,对...
这就是指令调整的 LLM 有用的地方,因为它们经过训练可以遵循自然语言指令并相应地生成代码片段。为了测试模型是否真的能理解人类意图并将其转化为代码,我们创建了,这是 BigCodeBench 的一个更具挑战性的变体,旨在评估指令调整的 LLM。 这些任务来自哪里?🤔 我们通过系统的“人类-LLM 协作过程”来保证 BigCodeBench...
我们相信,在 LLM 的推动下,软件行业也会迎来“Excel 时刻”:LLM 融入 IDE 后,入门级开发者甚至非技术背景用户也能够更好更快地实现程序编写,用户在代码编写中调用各种 LLM-based 服务、Code Agents 就像在Excel 里用使用公式一样简单。 因为流量和产品先发优势,IDE 目前几乎是被 Visual Studio 和 Github Copolit...
在几乎没有多样性的情况下,例如贪婪解码,从模型重复采样返回高度相似的程序,导致额外的推理时间计算的增益很小。这种多样性问题也反映在许多公共排行榜中(例如 LMSYS Chatbot Arena [14]、LiveCodeBench [22]、OpenLLMLeaderboard [1]),它们通常只报告来自模型的单个样本的 pass rate,忽略整个维度以及比较模型。虽然...
Since its inception in mid-2021, the HumanEval benchmark has not only become immensely popular but has also emerged as a quintessential evaluation tool for measuring the performance of LLMs in code generation tasks. The [leaderboard](https://paperswithcode.com/sota/code-generation-on-humaneval...
BigCodeBench: The Next Generation of HumanEval HumanEval is a reference benchmark for evaluating large language models (LLMs) on code generation tasks, as it makes the evaluation of compact function-level code snippets easy. However, there are growing concerns about its effectiveness in ...
BigCodeBench: The Next Generation of HumanEval HumanEval is a reference benchmark for evaluating large language models (LLMs) on code generation tasks, as it makes the evaluation of compact function-level code snippets easy. However, there are growing concerns about its effectiveness in...
Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks 7 Mar 2024 13 Previous 1 Next Showing 1 to 1 of 1 papers Dataset Loaders Edit No data loaders found. You can submit your data loader here. Tasks Edit Code Generation Code Completion Text-to-Code Generation Similar...
Create an LLM fine-tuning job using the AutoML API Supported models Dataset file types and input data format Hyperparameters Metrics Model deployment and predictions Create a Regression or Classification Job Using the Studio Classic UI Configure the default parameters of an Autopilot experiment (for ad...
Table 20: Performance on the Python portion of the CodeXGLUE Code Summarization task, evaluating function docstring generation. Models are evaluated zero-shot using their infilling capability.Model BLEU InCoder-6B 18.27 SantaCoder 19.74 StarCoderBase 21.38 StarCoder 21.99...