This is an evaluation harness for the HumanEval problem solving dataset described in the paper "Evaluating Large Language Models Trained on Code". It used to measure functional correctness for synthesizing programs from docstrings. It consists of 164 original programming problems, assessing language comp...
HumanEval was developed by OpenAI as an evaluation dataset specifically designed for large language models. It serves as a reference benchmark for evaluating LLMs on code generation tasks, focusing on the models' ability to comprehend language, reason, and solve problems related to algorithms and ...
HumanEval[1] 是 OpenAI 用来评估大语言模型生成代码能力的工具,包括手写的 164 个 python 编程问题及解答的 jsonl 格式数据,以及执行评估的脚本。
HumanEvalPack Introduced by Muennighoff et al. in OctoPack: Instruction Tuning Code Large Language Models HumanEvalPack is an extension of OpenAI's HumanEval to cover 6 total languages across 3 tasks. The evaluation suite is fully created by humans....
# determines how to combine results from each document in the dataset. # Check `lm_eval.metrics` to find built-in aggregation functions. return {} def higher_is_better(self): # TODO: For each (sub)metric in the task evaluation, add a key-value pair # with the metric name as key an...
HumanEval: Hand-Written Evaluation Set This is an evaluation harness for the HumanEval problem solving dataset described in the paper "Evaluating Large Language Models Trained on Code". Installation Make sure to use python 3.7 or later:
bash codefuseEval/script/generation.sh MODELNAME EVALDATASET OUTFILE LANGUAGE eg: bash codefuseEval/script/generation.sh CodeFuse-13B humaneval_python result/test.jsonl python 如果你想进行代码翻译评测,传入的语言参数为当前待翻译的代码语言,例如: 如果你想将C++代码翻译为Python代码,传入代码语言为CPP,如...
HumanEval: Hand-Written Evaluation Set Sandbox for Executing Generated Programs Code Fine-Tuning Data Collection Methods Results Comparative Analysis of Related Models and Systems Results on the APPS Dataset Supervised Fine-Tuning Problems from Competitive Programming Problems from Continuous Integration Filteri...
DataLoader: Train: dataset: name: MultiLabelDataset image_root: "dataset/pa100k/" #指定训练图片所在根路径 cls_label_path: "dataset/pa100k/train_list.txt" #指定训练列表文件位置 label_ratio: True transform_ops: Eval: dataset: name: MultiLabelDataset image_root: "dataset/pa100k/" #指定评估...
dataset and evaluation metrics and provides pointers into the dataset for additional details. It is our hope that HumanEva-I will become a standard dataset for the evaluation of articulated human motion and pose estimation. 1 Introduction The recovery of articulated human motion and pose from video...