{
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  "bskyPostRef": {
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    "uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mmuwdkjujdo2"
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  "path": "/t/built-a-browser-based-rl-training-platform-with-huggingface-model-sharing-feedback-welcome/176276#post_1",
  "publishedAt": "2026-05-28T00:04:43.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "agenlus.com",
    "Launching on Product Hunt soon"
  ],
  "textContent": "Hey HuggingFace community\n\nI’ve been working on Agenlus — a platform where you can train RL agents directly in your browser (no install, WebGPU-accelerated) and share your trained models to HuggingFace.\n\nThe idea is simple: train an agent on CartPole, MountainCar, or battle environments, then push your model straight to HF so others can load, compare, and build on it.\n\nRight now the flow is:\n\n  1. Train in browser → 2. Push to HuggingFace → 3. Others can load and battle your agent on the leaderboard\n\n\n\nThe HF integration was the piece I was most excited about — RL models have always been weirdly hard to share in a standardized way. HuggingFace already solved this for NLP and CV, so it felt natural to plug into that ecosystem for RL.\n\nWould love feedback from this community especially — are there model formats or metadata standards I should be following to make the models more useful/interoperable?\n\nagenlus.com  Launching on Product Hunt soon",
  "title": "Built a browser-based RL training platform with HuggingFace model sharing — feedback welcome"
}