{"data":{"slug":"nlpxucan-wizardlm","name":"WizardLM","tagline":"LLMs build upon Evol Insturct: WizardLM, WizardCoder, WizardMath","github_url":"https://github.com/nlpxucan/WizardLM","owner":"nlpxucan","repo":"WizardLM","owner_avatar_url":"https://avatars.githubusercontent.com/u/12636990?v=4","primary_language":"Python","stars":9479,"forks":747,"topics":[],"archived":false,"github_pushed_at":"2025-06-07T01:35:05+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/nlpxucan-wizardlm","markdown_url":"https://www.graphcanon.com/tools/nlpxucan-wizardlm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nlpxucan-wizardlm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nlpxucan-wizardlm","description":"LLMs build upon Evol Insturct: WizardLM, WizardCoder, WizardMath","homepage_url":null,"license":null,"open_issues":169,"watchers":107,"ai_summary":null,"readme_excerpt":"## WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions\n\n

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\nšŸ¤— HF Repo ā€¢ šŸ¦ Twitter ā€¢ šŸ“ƒ [WizardLM] @ICLR2024 ā€¢ šŸ“ƒ [WizardCoder] @ICLR2024 ā€¢ šŸ“ƒ [WizardMath]
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\n\"WizardLM\"\n

\n\n\n\n\n\n**Unofficial Video Introductions**\n\nThanks to the enthusiastic friends, their video introductions are more lively and interesting.\n1. [NEW WizardLM 70b šŸ”„ Giant Model...Insane Performance](https://www.youtube.com/watch?v=WdpiIXrO4_o)\n2. [GET WizardLM NOW! 7B LLM KING That Can Beat ChatGPT! I'm IMPRESSED!](https://www.youtube.com/watch?v=SaJ8wyKMBds)\n3. [WizardLM: Enhancing Large Language Models to Follow Complex Instructions](https://www.youtube.com/watch?v=I6sER-qivYk)\n4. [WizardCoder AI Is The NEW ChatGPT's Coding TWIN!](https://www.youtube.com/watch?v=XjsyHrmd3Xo)\n\n## News\n\n- šŸ”„šŸ”„šŸ”„[2024/01/04] We released **WizardCoder-33B-V1.1** trained from deepseek-coder-33b-base, the **SOTA OSS Code LLM** on [EvalPlus Leaderboard](https://evalplus.github.io/leaderboard.html), achieves **79.9 pass@1** on HumanEval, **73.2 pass@1** on HumanEval-Plus, **78.9 pass@1** on MBPP, and **66.9 pass@1** on MBPP-Plus. **WizardCoder-33B-V1.1** outperforms **ChatGPT 3.5**, **Gemini Pro**, and **DeepSeek-Coder-33B-instruct** on HumanEval and HumanEval-Plus pass@1. **WizardCoder-33B-V1.1** is comparable with **ChatGPT 3.5**, and surpasses **Gemini Pro** on MBPP and MBPP-Plus pass@1.\n- [2023/08/26] We released **WizardCoder-Python-34B-V1.0** , which achieves the **73.2 pass@1** and surpasses **GPT4 (2023/03/15)**, **ChatGPT-3.5**, and **Claude2** on the [HumanEval Benchmarks](https://github.com/openai/human-eval). For more details, please refer to [WizardCoder](https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder).\n- [2023/06/16] We released **WizardCoder-15B-V1.0** , which surpasses **Claude-Plus (+6.8)**, **Bard (+15.3)** and **InstructCodeT5+ (+22.3)** on the [HumanEval Benchmarks](https://github.com/openai/human-eval). For more details, please refer to [WizardCoder](https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder).\n\n\n| Model | Checkpoint | Paper | HumanEval | HumanEval+ | MBPP | MBPP+ |\n| ----- |------| ---- |------|-------| ----- | ----- |\n| GPT-4-Turbo (Nov 2023) | - | - | 85.4 | 81.7 | 83.0 | 70.7 |\n| GPT-4 (May 2023) | - | - | 88.4 | 76.8 | - | - |\n| GPT-3.5-Turbo (Nov 2023) | - | - | 72.6 | 65.9 | 81.7 | 69.4 |\n| Gemini Pro | - | - | 63.4 | 55.5 | 72.9 | 57.9 |\n| DeepSeek-Coder-33B-instruct | - | - | 78.7 | 72.6 | 78.7 | 66.7 |\n| WizardCoder-33B-V1.1 | šŸ¤— HF Link | šŸ“ƒ [WizardCoder] | 79.9 | 73.2 | 78.9 | 66.9 |\n| WizardCoder-Python-34B-V1.0 | šŸ¤— HF Link | šŸ“ƒ [WizardCoder] | 73.2 | 64.6 | 73.2 | 59.9 |\n| WizardCoder-15B-V1.0 | šŸ¤— HF Link | šŸ“ƒ [WizardCoder] | 59.8 | 52.4 | -- | -- |\n| WizardCoder-Pyth","github_created_at":"2023-04-23T13:26:46+00:00","created_at":"2026-07-11T23:44:17.391083+00:00","updated_at":"2026-07-11T23:44:21.570218+00:00","categories":[{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"python","name":"python"}],"trust":{"provenance":{"is_fork":false,"github_id":631580207,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:44:18.604Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":399,"last_release_at":"2023-08-27T10:47:33Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:44:19.062Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T23:44:18.379Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-11T23:44:18.379Z"}}}}