Launching today
Arkor
Fine-tune and Deploy Open-weight Models in TypeScript
130 followers
Fine-tune and Deploy Open-weight Models in TypeScript
130 followers
Start a real LLM training in 10 minutes. Tell Claude Code or Codex what the model is for; they prepare the datasets and create the training project. Click "Run Training" in the local studio. Arkor runs the training, and deploys the trained model as an OpenAI-compatible API. Think Next.js and Vercel for fine-tuning: code you can review, infrastructure you do not have to manage, and a model your app can call. No GPU setup. No ML expertise required. No Python training code to write.
can you download the resulting weights?
Arkor
@school_4_ants Thanks for asking, Hunter!
Not yet in the current release.
We launched managed-first so people could go from training to inference without setting up GPUs or deployment infrastructure.
That said, avoiding vendor lock-in is important to us, and downloadable training artifacts are on our roadmap.
For your use case, would downloading the LoRA adapter be enough, or would you also need the merged model weights?
And would Hugging Face / safetensors be your preferred format?
Fine-tuning open-weight models in TypeScript is kind of unusual approach, most tooling for this is Python heavy. Makes it much more accesible for JS devs though. What models are supported so far?
Pushing a fine-tune through without touching a single Python script felt weirdly good. The handoff between Claude Code preparing the data and Arkor just clicking "Run Training" was exactly the kind of low-friction flow I keep wishing existed.