Console

Fine Tuning as a Service

Register a dataset, choose a framework & PEFT technique, run real fine-tuning (torch / transformers / peft / TRL), track with MLflow, deploy, and prompt the adapted model.

1. Register dataset

Datasets

2. Create fine-tune job

Jobs

JobModelFW / TechStatusMetrics / ErrorPipeline
No jobs yet

3. Deploy model

4. Prompt (UI / API)

Catalog

transformers trl verl llama-factory unsloth axolotl

Roadmap

  1. Phase 0 — Fine-Tuning & RL Templates (available)
  2. Phase 1 — Fine-Tuning UI (available)
  3. Phase 2 — Fine-Tune & Evaluate (available)
  4. Phase 3 — Resource Optimization (planned)
  5. Phase 4 — Sweeps & Optimization (planned)