### [Commissioned](https://free.ilovefree.com/)

**Published:** 2026-06-09T08:12:00

**Author:** ilovefree

**Excerpt:** Freemium + from $25/mo. Commissioned.tech: no-code fine-tuning of OpenAI/Google/open-source models via LoRA. Claims <5 min training, downloadable adapters. No Refunds policy. 24K+ TAAFT views.

Fine-tuning a language model typically costs **$50–$300 per training run** and takes days of data preparation. [Commissioned.tech](https://www.commissioned.tech/?ref=ilovefree&utm_source=ilovefree&utm_medium=referral) claims to compress this into **under 5 minutes** with no coding or data formatting — starting at **$25/month** for paid plans.

### How the Fine-Tuning Pipeline Works

Upload documents (PDF, CSV, or other formats) and the platform automatically cleans, formats, and structures the data for training. It supports models from **OpenAI**, **Google**, and the **open-source community**. For open-source models, it uses **LoRA** (Low-Rank Adaptation) — a technique that freezes base model weights and trains only a small adapter layer, reducing compute and training time. The adapter can be **downloaded and run on your own hardware** after training, so you’re not locked into Commissioned’s cloud for inference.

## Two Workflows

1.  **Style/content adherence**: Upload writing samples (emails, blog posts, roleplay scripts) to create a model matching your voice — better tone consistency than prompt engineering alone.
2.  **Classification and labeling**: Upload a CSV with input/output columns, and Commissioned trains a model for labeling tasks — document classification, sentiment tagging, or data extraction.

### Tier Comparison

| Plan | Price | Notes |
| :--- | :--- | :--- |
| Freemium | $0  | Limited features |
| Paid | From $25/mo | Full fine-tuning capabilities |
| Refund Policy | **No Refunds** | All sales final |

The freemium tier lets you test before upgrading. The No Refunds policy is worth noting — if the fine-tuned model underperforms, you’re out the money.

## The Catch

-   **Limited model support**: Covers OpenAI, Google, and select open-source models only. Users needing specific architectures (Llama 4, DeepSeek, Mistral) should verify compatibility before subscribing.
-   **Too automated for practitioners**: No access to hyperparameters, training loops, or intermediate results. Community reviews flagged this as a con — fine for non-technical users, limiting for data scientists.
-   **Cloud-dependent training**: Fine-tuning runs on Commissioned’s infrastructure. Organizations with air-gapped environments can download the LoRA adapter post-training but can’t train on-premise.
-   **Oversimplification risk**: The automated pipeline abstracts away ML decisions that experienced practitioners would want to control.
-   **Early-stage product**: **24,263 views** and only **12 saves** since February 2026. Instagram shows **54 followers** with **0 posts**.
-   **Website access issues**: commissioned.tech returned a **403 Forbidden** error during independent testing, raising availability questions.

**Visit [Commissioned](https://www.commissioned.tech/?ref=ilovefree&utm_source=ilovefree&utm_medium=referral)** — https://www.commissioned.tech/

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