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 | Name | Training Dataset | Training Status | Deployment Status | Created By | Created At | |
|---|---|---|---|---|---|---|---|---|
| meta-llama/Llama-3.2-1B-Instruct | mathi-slight-olive-minnow | (fb6e86)sql-create-context.parquet | Stopped | Not Deployed | mathi | 5 months ago | ||
| meta-llama/Llama-3.2-1B-Instruct | (fb6e86)sql-create-context_test_3k.parquet | Failed | Not Deployed | mathi | 5 months ago | |||
| openai/gpt-oss-20b | (fb6e86)sql-create-context_train_10k.parquet | Failed | Not Deployed | mathi | 5 months ago | |||
| openai/gpt-oss-20b | (fb6e86)sql-create-context_train_10k.parquet | Stopped | Not Deployed | mathi | 5 months ago | |||
| openai/gpt-oss-20b | mathi-big-olive-gorilla | (fb6e86)sql-create-context_train_10k.parquet | Success | Sleeping | mathi | 6 months ago | ||
| openai/gpt-oss-20b | (fb6e86)sql-create-context_train_10k.parquet | Failed | Not Deployed | mathi | 6 months ago |