{"id":13450957,"url":"https://github.com/stanford-crfm/helm","last_synced_at":"2025-05-13T16:10:08.844Z","repository":{"id":63370800,"uuid":"432968463","full_name":"stanford-crfm/helm","owner":"stanford-crfm","description":"Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducible and transparent evaluation of foundation models, including large language models (LLMs) and multimodal models.","archived":false,"fork":false,"pushed_at":"2025-05-12T06:54:15.000Z","size":119928,"stargazers_count":2215,"open_issues_count":145,"forks_count":292,"subscribers_count":38,"default_branch":"main","last_synced_at":"2025-05-12T07:42:39.761Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://crfm.stanford.edu/helm","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/stanford-crfm.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.bib","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2021-11-29T08:53:17.000Z","updated_at":"2025-05-12T06:54:16.000Z","dependencies_parsed_at":"2023-09-26T17:15:54.838Z","dependency_job_id":"76078d8a-28a5-4866-9211-8e1d2d85c297","html_url":"https://github.com/stanford-crfm/helm","commit_stats":{"total_commits":3007,"total_committers":62,"mean_commits":48.5,"dds":0.6544728965746591,"last_synced_commit":"84b69f1ceb6d56e06f710a6c61cffed2b7e61bcc"},"previous_names":[],"tags_count":14,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stanford-crfm%2Fhelm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stanford-crfm%2Fhelm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stanford-crfm%2Fhelm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stanford-crfm%2Fhelm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/stanford-crfm","download_url":"https://codeload.github.com/stanford-crfm/helm/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253980055,"owners_count":21994042,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-07-31T07:00:40.823Z","updated_at":"2025-05-13T16:10:03.829Z","avatar_url":"https://github.com/stanford-crfm.png","language":"Python","funding_links":[],"categories":["Evaluation","🤖 LLM \u0026 Chatbot Testing","Benchmarking \u0026 Evaluation","Tools","LLM Evaluation","Python","A01_文本生成_文本对话","Benchmarks \u0026 Evaluation","Evaluation and Monitoring","Testing \u0026 Evaluation","LLM Evaluation:","Benchmarks and Evaluation","Model Evaluation \u0026 Benchmarking","9. Evaluation, Benchmarks \u0026 Datasets","3）参考实现与开源工具（GitHub）"],"sub_categories":["Papers/Methods","大语言对话模型及数据","Evaluation Frameworks","LLM Evaluations and Benchmarks","LangManus","评测框架与 Agent Benchmarks"],"readme":"# Holistic Evaluation of Language Models (HELM)\n\n\n\u003ca href=\"https://github.com/stanford-crfm/helm\"\u003e\n    \u003cimg alt=\"GitHub Repo stars\" src=\"https://img.shields.io/github/stars/stanford-crfm/helm\"\u003e\n\u003c/a\u003e\n\u003ca href=\"https://github.com/stanford-crfm/helm/graphs/contributors\"\u003e\n    \u003cimg alt=\"GitHub contributors\" src=\"https://img.shields.io/github/contributors/stanford-crfm/helm\"\u003e\n\u003c/a\u003e\n\u003ca href=\"https://github.com/stanford-crfm/helm/actions/workflows/test.yml?query=branch%3Amain\"\u003e\n    \u003cimg alt=\"GitHub Actions Workflow Status\" src=\"https://img.shields.io/github/actions/workflow/status/stanford-crfm/helm/test.yml\"\u003e\n\u003c/a\u003e\n\u003ca href=\"https://crfm-helm.readthedocs.io/en/latest/\"\u003e\n    \u003cimg alt=\"Documentation Status\" src=\"https://readthedocs.org/projects/helm/badge/?version=latest\"\u003e\n\u003c/a\u003e\n\u003ca href=\"https://github.com/stanford-crfm/helm/blob/main/LICENSE\"\u003e\n    \u003cimg alt=\"License\" src=\"https://img.shields.io/github/license/stanford-crfm/helm?color=blue\" /\u003e\n\u003c/a\u003e\n\u003ca href=\"https://pypi.org/project/crfm-helm/\"\u003e\n    \u003cimg alt=\"PyPI\" src=\"https://img.shields.io/pypi/v/crfm-helm?color=blue\" /\u003e\n\u003c/a\u003e\n\n[comment]: \u003c\u003e (When using the img tag, which allows us to specify size, src has to be a URL.)\n\u003cimg src=\"https://github.com/stanford-crfm/helm/raw/v0.5.4/helm-frontend/src/assets/helm-logo.png\" alt=\"HELM logo\"  width=\"480\"/\u003e\n\n**Holistic Evaluation of Language Models (HELM)** is an open source Python framework created by the [Center for Research on Foundation Models (CRFM) at Stanford](https://crfm.stanford.edu/) for holistic, reproducible and transparent evaluation of foundation models, including large language models (LLMs) and multimodal models. This framework includes the following features:\n\n- Datasets and benchmarks in a standardized format (e.g. MMLU-Pro, GPQA, IFEval, WildBench)\n- Models from various providers accessible through a unified interface (e.g. OpenAI models, Anthropic Claude, Google Gemini)\n- Metrics for measuring various aspects beyond accuracy (e.g. efficiency, bias, toxicity)\n- Web UI for inspecting individual prompts and responses\n- Web leaderboard for comparing results across models and benchmarks\n\n## Documentation\n\nPlease refer to [the documentation on Read the Docs](https://crfm-helm.readthedocs.io/) for instructions on how to install and run HELM.\n\n## Quick Start\n\n\u003c!--quick-start-begin--\u003e\n\nInstall the package from PyPI:\n\n```sh\npip install crfm-helm\n```\n\nRun the following in your shell:\n\n```sh\n# Run benchmark\nhelm-run --run-entries mmlu:subject=philosophy,model=openai/gpt2 --suite my-suite --max-eval-instances 10\n\n# Summarize benchmark results\nhelm-summarize --suite my-suite\n\n# Start a web server to display benchmark results\nhelm-server --suite my-suite\n```\n\nThen go to http://localhost:8000/ in your browser.\n\n\u003c!--quick-start-end--\u003e\n\n## Leaderboards\n\nWe maintain offical leaderboards with results from evaluating recent models on notable benchmarks using this framework. Our current flagship leaderboards are:\n\n- [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/)\n- [HELM Safety](https://crfm.stanford.edu/helm/safety/latest/)\n- [Holistic Evaluation of Vision-Language Models (VHELM)](https://crfm.stanford.edu/helm/vhelm/latest/)\n\nWe also maintain leaderboards for a diverse range of domains (e.g. medicine, finance) and aspects (e.g. multi-linguality, world knowledge, regulation compliance). Refer to the [HELM website](https://crfm.stanford.edu/helm/) for a full list of leaderboards.\n\n## Papers\n\nThe HELM framework was used in the following papers for evaluating models.\n\n- **Holistic Evaluation of Language Models** - [paper](https://openreview.net/forum?id=iO4LZibEqW), [leaderboard](https://crfm.stanford.edu/helm/classic/latest/)\n- **Holistic Evaluation of Vision-Language Models (VHELM)** - [paper](https://arxiv.org/abs/2410.07112), [leaderboard](https://crfm.stanford.edu/helm/vhelm/latest/), [documentation](https://crfm-helm.readthedocs.io/en/latest/vhelm/)\n- **Holistic Evaluation of Text-To-Image Models (HEIM)** - [paper](https://arxiv.org/abs/2311.04287), [leaderboard](https://crfm.stanford.edu/helm/heim/latest/), [documentation](https://crfm-helm.readthedocs.io/en/latest/heim/)\n- **Image2Struct: Benchmarking Structure Extraction for Vision-Language Models** - [paper](https://arxiv.org/abs/2410.22456)\n- **Enterprise Benchmarks for Large Language Model Evaluation** - [paper](https://arxiv.org/abs/2410.12857), [documentation](https://crfm-helm.readthedocs.io/en/latest/enterprise_benchmark/)\n- **The Mighty ToRR: A Benchmark for Table Reasoning and Robustness** - [paper](https://arxiv.org/abs/2502.19412)\n- **Reliable and Efficient Amortized Model-based Evaluation** - [paper](https://arxiv.org/abs/2503.13335), [documentation](https://crfm-helm.readthedocs.io/en/latest/reeval/)\n\nThe HELM framework can be used to reproduce the published model evaluation results from these papers. To get started, refer to the documentation links above for the corresponding paper, or the [main Reproducing Leaderboards documentation](https://crfm-helm.readthedocs.io/en/latest/reproducing_leaderboards/).\n\n## Citation\n\nIf you use this software in your research, please cite the [Holistic Evaluation of Language Models paper](https://openreview.net/forum?id=iO4LZibEqW) as below.\n\n```bibtex\n@article{\nliang2023holistic,\ntitle={Holistic Evaluation of Language Models},\nauthor={Percy Liang and Rishi Bommasani and Tony Lee and Dimitris Tsipras and Dilara Soylu and Michihiro Yasunaga and Yian Zhang and Deepak Narayanan and Yuhuai Wu and Ananya Kumar and Benjamin Newman and Binhang Yuan and Bobby Yan and Ce Zhang and Christian Alexander Cosgrove and Christopher D Manning and Christopher Re and Diana Acosta-Navas and Drew Arad Hudson and Eric Zelikman and Esin Durmus and Faisal Ladhak and Frieda Rong and Hongyu Ren and Huaxiu Yao and Jue WANG and Keshav Santhanam and Laurel Orr and Lucia Zheng and Mert Yuksekgonul and Mirac Suzgun and Nathan Kim and Neel Guha and Niladri S. Chatterji and Omar Khattab and Peter Henderson and Qian Huang and Ryan Andrew Chi and Sang Michael Xie and Shibani Santurkar and Surya Ganguli and Tatsunori Hashimoto and Thomas Icard and Tianyi Zhang and Vishrav Chaudhary and William Wang and Xuechen Li and Yifan Mai and Yuhui Zhang and Yuta Koreeda},\njournal={Transactions on Machine Learning Research},\nissn={2835-8856},\nyear={2023},\nurl={https://openreview.net/forum?id=iO4LZibEqW},\nnote={Featured Certification, Expert Certification}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstanford-crfm%2Fhelm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstanford-crfm%2Fhelm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstanford-crfm%2Fhelm/lists"}