Lumino AI

What it does

SDK and web console! Using our SDK, everyone can now fine-tune LLMs like Llama 3.1 with just a few lines of code! You don’t have to set up compute instances, build ML infra, or it's up to 80% cheaper than AWS/GCP!

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  LLM fine-tuning SDK and would love your feedback2024 · docs.luminolabs.ai · ▲14

  We’ve built a LLM fine-tuning SDK that supports Llama 3.1 right now. We’d love your feedback, and are happy to give extra free credits if you try the product and jump on a 15 minute call and provide feedback :)

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  Taylor AI2023 · trytaylor.ai · ▲118

  Fine-tune open source LLMs in minutes

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  Gradient2023 · hyperagent.com · ▲153

  Developer API for building private LLMs that you own

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  Why write code if the LLM can just do the thing? (web app experiment)Nov 2025 · github.com · ▲436

  I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…

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  LlamaGym – fine-tune LLM agents with online reinforcement learning2024 · github.com · ▲239

  Fine-tune LLM agents with online reinforcement learning - KhoomeiK/LlamaGym

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  Tune LLaMa3.1 on Google Cloud TPUs2024 · github.com · ▲189

  Hey HN, we wanted to share our repo where we fine-tuned Llama 3.1 on Google TPUs. We’re building AI infra to fine-tune and serve LLMs on non-NVIDIA GPUs (TPUs, Trainium, AMD GPUs). The problem: Right now, 90% of LLM workloads run on NVIDIA GPUs, but there are equally powerful and more cost-effective alternatives out there. For example, training and serving Llama 3.1 on Google TPUs is about 30% cheaper than NVIDIA GPUs. But developer tooling for non-NVIDIA chipsets is lacking. We felt this pain ourselves. We initially tried using PyTorch XLA to train Llama 3.1 on TPUs, but it was rough: xla…

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