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| title: HuggingEnvs | |
| emoji: 🤗 | |
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| colorTo: purple | |
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| license: mit | |
|  | |
| [](https://github.com/adithya-s-k/HuggingEnvs) | |
| [](https://huggingface.co/spaces/AdithyaSK/rl-environments-guide) | |
| [](https://huggingface.co/spaces/AdithyaSK/rl-environments-101-slides) | |
| # 🤗 HuggingEnvs: Open RL Environments | |
| HuggingEnvs is a home for **end-to-end RL environment recipes**, built to make it easier to **explore, reproduce, train, and evaluate agent systems**. | |
| Explore complete and reproducible environment projects from us and the community, including: | |
| * 🌍 **Open RL environments** | |
| * 🧩 **End-to-end environment recipes** | |
| * 💻 **Complete implementations** | |
| * 📦 **Models, datasets, and artifacts** | |
| * 🧪 **Training and evaluation setups** | |
| * 🚀 **Demos and Spaces** | |
| * 📚 **Tutorials and guides** | |
| All the reproducible code — environments, rollouts, training configs, notebooks, article and slide sources — lives in one repo: **[github.com/adithya-s-k/HuggingEnvs](https://github.com/adithya-s-k/HuggingEnvs)**. The artifacts those produce live here on the Hub. | |
| # HuggingEnvs Projects | |
| A growing collection of open projects, environments, resources, and artifacts. | |
| | Project | What it is | Explore | | |
| | :------------------------- | :----------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------ | | |
| | **HuggingEnvs Academy** | Articles, guides, tutorials, slides, and hands-on resources for learning how to build RL environments and agent systems. | [Explore →](https://huggingface.co/collections/HuggingEnvs/huggingenvs-academy) | | |
| | **Data Agent** | Training SLMs for data science with multi-harness RL environments. | [Explore →](https://huggingface.co/collections/HuggingEnvs/data-agent) | | |
| # Articles & Talks | |
| | | What it covers | Read / Watch | | |
| | :--- | :--- | :--- | | |
| | 📖 **The Ultimate Guide to RL Environments** | Building and scaling RL environments in the LLM era — how frameworks are built, how rewards are wired, how they scale to thousands of concurrent sessions. | [Read →](https://huggingface.co/spaces/AdithyaSK/rl-environments-guide) | | |
| | 🎞️ **RL Environments 101** | From "what is an env?" to training your own: RL fundamentals → environment anatomy → OpenEnv → training with TRL. | [Watch →](https://huggingface.co/spaces/AdithyaSK/rl-environments-101-slides) | | |
| | 📈 **Scaling RL for LLMs** | RL environments and RL training — what an environment is, how reward hacking happens, how to train against your own. AMD AI Dev Day. | [Watch →](https://huggingface.co/spaces/AdithyaSK/scaling-rl-for-llms-amd-ai-dev-day) | | |
| | 🔀 **Multi-Harness Training** | OpenEnv × Harbor — why an environment's failure model decides whether it can be trained against. | [Watch →](https://huggingface.co/spaces/AdithyaSK/multi-harness-training-slides) | | |
| # Environments | |
| Three reference environments, each implemented across six frameworks — `openenv`, `ors`, `nemo_gym`, `verifiers`, `skyrl_gym`, `gem`. Same logic, six dialects. [Source →](https://github.com/adithya-s-k/HuggingEnvs/tree/main/00-environments-101) | |
| | Environment | Tools | OpenEnv | ORS | NeMo Gym | | |
| | :--- | :--: | :--- | :--- | :--- | | |
| | **Jupyter agent** — real code execution in an E2B sandbox | 4 | [Space](https://huggingface.co/spaces/AdithyaSK/jupyter-agent-openenv) | [Space](https://huggingface.co/spaces/AdithyaSK/jupyter-agent-ors) | [Space](https://huggingface.co/spaces/AdithyaSK/jupyter-agent-nemo-gym) | | |
| | **Wordle** — multi-turn, pure Python, no backend | 1 | [Space](https://huggingface.co/spaces/AdithyaSK/wordle-openenv) | [Space](https://huggingface.co/spaces/AdithyaSK/wordle-ors) | [Space](https://huggingface.co/spaces/AdithyaSK/wordle-nemo-gym) | | |
| | **Desktop** — computer-use, vision-driven Linux desktop | 19 | [Space](https://huggingface.co/spaces/AdithyaSK/desktop-openenv) | [Space](https://huggingface.co/spaces/AdithyaSK/desktop-ors) | — | | |
| # Build your own | |
| Five agent skills turn a plain-English description into a runnable RL environment across four frameworks — works with Claude Code, Cursor, Codex, OpenCode, Gemini CLI and others. | |
| ```bash | |
| npx skills add adithya-s-k/HuggingEnvs | |
| ``` | |
| **We're looking for new end-to-end recipes** — a task, an environment, a training run, and honest results. [Contributing guide →](https://github.com/adithya-s-k/HuggingEnvs/blob/main/CONTRIBUTING.md) | |