TuneSalon AI

TuneSalon AI provides a web‑based workflow for fine‑tuning open‑source large language models on cloud GPUs without writing code. Users upload documents or generate training data with an integrated dataset generator, select a model ranging from 3 billion to 35 billion parameters (such as Qwen, Mistral, or Gemma), and initiate a one‑click training job on A100 or H200 GPUs. After training, the customized model can be saved in the user’s library, accessed through a chat interface, or exported in GGUF format for deployment elsewhere.

The platform targets developers and teams who want to create domain‑specific or on without needing expertise in machine‑learning infrastructure. It abstracts the steps of data preparation, model selection, and LoRA‑based fine‑tuning, handling GPU provisioning and storage automatically. Users can browse community adapters, manage their own models, and purchase compute credits on a pay‑as‑you‑go basis.

Distinctive aspects include the entirely no‑code interface, the ability to fine‑tune multiple curated open‑source models on high‑end cloud GPUs, and the option to export the resulting adapter as a portable GGUF file for use outside the service.