On Oxen.ai, fine-tuning is as easy as uploading your dataset, selecting a model, and kicking off a job. The dataset can be any of the supported tabular file formats such as csv, tsv, json, or parquet. Learn more about fine-tuning in our developer docs.
Existing fine-tunes
6| ID | Base Model | Model Name | Display Name | Training Dataset | Training Status | Deployment Status | Created By | Created At | |
|---|---|---|---|---|---|---|---|---|---|
| black-forest-labs/FLUX.2-dev | 6829217bimages.parquet | Success | Not Deployed | subygan | 5 days ago | ||||
| black-forest-labs/FLUX.1-dev | 6829217bimages.parquet | Success | Not Deployed | subygan | 3 weeks ago | ||||
| Qwen/Qwen3-0.6B | 85e50593images.parquet | Success | Not Deployed | subygan | 1 month ago | ||||
| Wan-AI/Wan2.1-T2V-1.3B-Diffusers | 85e50593images.parquet | Stopped | Not Deployed | subygan | 2 months ago | ||||
| Qwen/Qwen-Image-Edit | a8749432images.parquet | Success | Not Deployed | subygan | 3 months ago | ||||
| Wan-AI/Wan2.2-T2V-A14B-Diffusers | d26db329images.parquet | Success | Not Deployed | subygan | 3 months ago |