{"data":{"slug":"oumi-ai-oumi","name":"oumi","tagline":"Easily fine-tune, evaluate and deploy open source LLMs/VLMs","github_url":"https://github.com/oumi-ai/oumi","owner":"oumi-ai","repo":"oumi","owner_avatar_url":"https://avatars.githubusercontent.com/u/167452922?v=4","primary_language":"Python","stars":9376,"forks":784,"topics":["dpo","evaluation","fine-tuning","gpt-oss","gpt-oss-120b","gpt-oss-20b","inference","llama","llms","open-weight","open-weight-models","open-weights","sft","slms","vlms"],"archived":false,"github_pushed_at":"2026-08-21T23:11:35+00:00","maintenance_label":"Very active","stars_delta_30d":17,"url":"https://www.graphcanon.com/tools/oumi-ai-oumi","markdown_url":"https://www.graphcanon.com/tools/oumi-ai-oumi.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/oumi-ai-oumi","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=oumi-ai-oumi","description":"Easily fine-tune, evaluate and deploy Qwen, Gemma, or any open weight LLM!","homepage_url":"https://oumi.ai","license":"Apache-2.0","open_issues":34,"watchers":63,"ai_summary":"A comprehensive tool for the management and deployment of various open-source language models (LLMs) including Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others.","readme_excerpt":"## 🚀 Getting Started\n\n| **Notebook** | **Try in Colab** | **Goal** |\n|----------|--------------|-------------|\n| **🎯 Getting Started: A Tour** | <a target=\"_blank\" href=\"https://colab.research.google.com/github/oumi-ai/oumi/blob/main/notebooks/Oumi - A Tour.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> | Quick tour of core features: training, evaluation, inference, and job management |\n| **🔧 Model Finetuning Guide** | <a target=\"_blank\" href=\"https://colab.research.google.com/github/oumi-ai/oumi/blob/main/notebooks/Oumi - Finetuning Tutorial.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> | End-to-end guide to LoRA tuning with data prep, training, and evaluation |\n| **📚 Model Distillation** | <a target=\"_blank\" href=\"https://colab.research.google.com/github/oumi-ai/oumi/blob/main/notebooks/Oumi - Distill a Large Model.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> | Guide to distilling large models into smaller, efficient ones |\n| **📋 Model Evaluation** | <a target=\"_blank\" href=\"https://colab.research.google.com/github/oumi-ai/oumi/blob/main/notebooks/Oumi - Evaluation with Oumi.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> | Comprehensive model evaluation using Oumi's evaluation framework |\n| **☁️ Remote Training** | <a target=\"_blank\" href=\"https://colab.research.google.com/github/oumi-ai/oumi/blob/main/notebooks/Oumi - Running Jobs Remotely.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> | Launch and monitor training jobs on cloud (AWS, Azure, GCP, Lambda, etc.) platforms |\n| **📈 LLM-as-a-Judge** | <a target=\"_blank\" href=\"https://colab.research.google.com/github/oumi-ai/oumi/blob/main/notebooks/Oumi - Simple Judge.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> | Filter and curate training data with built-in judges |\n\n---\n\n### Installation\n\nChoose the installation method that works best for you:\n\n<details open>\n<summary><b>Using pip (Recommended)</b></summary>\n\n```bash\n\n---\n\n## 📜 License\n\nThis project is licensed under the Apache License 2.0. See the [LICENSE](LICENSE) file for details.\n\n[^1]: Open models are defined as models with fully open weights, training code, and data, and a permissive license. See [Open Source Definitions](https://opensource.org/ai) for more information.","github_created_at":"2024-05-07T17:45:15+00:00","created_at":"2026-07-11T11:37:07.569447+00:00","updated_at":"2026-08-23T18:00:58.136185+00:00","categories":[{"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"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"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"}],"tags":[{"slug":"dpo","name":"dpo"},{"slug":"evaluation","name":"evaluation"},{"slug":"fine-tuning","name":"fine-tuning"},{"slug":"llms","name":"llms"},{"slug":"sft","name":"sft"},{"slug":"vlms","name":"vlms"}],"trust":{"provenance":{"is_fork":false,"github_id":797371964,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-23T18:00:57.340Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":1,"last_release_at":"2026-05-07T17:02:19Z","stars_delta_30d":17,"open_issues_delta_30d":3},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:37:08.953Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-23T18:00:57.803Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-23T18:00:57.803Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-23T18:00:57.803Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-23T18:00:57.803Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-23T18:00:57.803Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-23T18:00:57.803Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Docker is used for standardized and portable environment deployments."],"requires_docker":true},"constraints":{"requires_docker":true},"when_to_use":["- You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants.","- Your project requires a dedicated tool that offers specific fine-tuning and evaluation functionalities for a wide range of language models."],"when_not_to_use":["- If your focus is on proprietary models rather than open-source ones, Oumi may not offer the necessary support or integrations.","- You require deployment flexibility beyond what Oumi provides for less commonly supported open-source LLMs outside its primary focus (e.g., Gemma 4, Qwen series)."],"source":"enrich:decision_facts","observed_at":"2026-07-12T12:29:30.618Z"},"constraint_facets":{"requires_docker":true},"decision_summary":[{"label":"Requirements","value":"Requires Docker; Docker is used for standardized and portable environment deployments."},{"label":"Adopt for","value":"Oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others."},{"label":"License detail","value":"Oumi is released under Apache-2.0 license, providing users with a permissive free software license that includes the terms of the MIT License while also addressing patent liability issues."}]}}