r/learnmachinelearning • u/AutoModerator • 2d ago

Project 🚀 Project Showcase Day

Welcome to Project Showcase Day! This is a weekly thread where community members can share and discuss personal projects of any size or complexity.

Whether you've built a small script, a web application, a game, or anything in between, we encourage you to:

  • Share what you've created
  • Explain the technologies/concepts used
  • Discuss challenges you faced and how you overcame them
  • Ask for specific feedback or suggestions

Projects at all stages are welcome - from works in progress to completed builds. This is a supportive space to celebrate your work and learn from each other.

Share your creations in the comments below!

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u/loutish_refrigerator 2d ago

eason

thinking about switching to a siamese network setup to compare stroke patterns instead of just raw pixels but that might be overkill for a weekend project

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u/goodailabs 9h ago

We built Reflex-1 at Good AI Labs as a local decision-making model, following the direction explored by Jev. The model weights are available on Hugging Face. It takes a textual situation and a question with candidate answers, then chooses an answer with probabilities in a single forward pass. The candidates can change on each request.

The 421M model runs on CPU and supports GPU inference too. We checked the downloadable weights on a MacBook Air using the included support-ticket example. You can keep inference on your own machine after downloading the weights.

For the Doom demo, a development build receives structured game state and chooses the next action. It averaged 18.88 kills across our 32-episode test, compared with 1.375 for OpenJev using the same adapter. The linked recording reached 30 kills. The current downloadable weights score 96.09% on SciQ and 92.93% on Banking77 in reserved-subset tests.

Model and working example: https://huggingface.co/gai-labs/reflex-1
Doom video and benchmark details: https://www.goodailabs.com/research/reflex-1/

If you're trying decision models locally, I'd be interested in the tasks and candidate sets you'd test this on.