Your First Model
A detailed walkthrough of uploading data and creating your first fine-tuned model.
Before you start
Have your data ready. If you're just experimenting, any of these will work:
- A few blog posts or essays you've written (
.txtor.md) - Chat or email transcripts (
.jsonlor.txt) - Documentation or notes (
.pdfor.md) - Code files (
.txt)
Don't worry about formatting. Commissioned handles cleaning, structuring, and deduplicating your data automatically. Raw, messy files are fine.
Step-by-step
Upload files
Drag and drop files into the upload area, or click to browse. You can upload multiple files at once.
Supported formats: JSONL, JSON, PDF, TXT, Markdown
Size limit: 5 GB per file
The upload card shows a preview of your selected files with names and sizes. You can remove individual files before submitting.
Write your use-case description
This is the most important input besides your data. The description tells Commissioned how to structure your data for training.
Good descriptions are specific:
| ❌ Vague | ✅ Specific |
|---|---|
| "Make a chatbot" | "Create a customer support agent that answers questions about our SaaS product using the attached help docs and past ticket transcripts" |
| "Writing helper" | "I want a writing assistant that matches the academic tone and citation style in these research papers" |
| "Code assistant" | "Fine-tune a coding assistant that follows our team's TypeScript conventions and knows our internal API from these docs" |
Select a base model
Choose which LLM to fine-tune. See Models for a detailed comparison.
Quick recommendations:
- First time? → GPT-4.1 Mini (fast, free, solid quality)
- Need the best quality? → GPT-4.1 or Gemini 2.5 Pro
- Want to self-host? → Qwen 3 8B (produces a downloadable LoRA adapter)
- Have very long documents? → Gemini 2.5 Flash
Submit and wait
Click Create a Custom Model. Your model card appears in the left panel with real-time status updates:
| Status | What's happening |
|---|---|
| Queued | Job is waiting to start |
| Validating files | Data is being parsed and cleaned |
| In progress | Model is actively training |
| Succeeded | Done — ready to use |
| Failed | Something went wrong |
Training times:
- GPU / Qwen: ~5 minutes
- OpenAI / Gemini: 30–45 minutes
You'll receive an email notification when training completes.
After training completes
Once your model shows Succeeded, you can:
- Chat with it — click Open in chat to start a conversation right in the browser
- Call it via API — generate an API key and use the OpenAI-compatible endpoint
- Rename it — click the rename action on the model card for better organization
- Download the adapter — for Qwen models, download the LoRA weights to self-host
Troubleshooting
Model shows "Failed"
Common causes:
- Not enough usable text — your files need enough content for training (a few hundred lines minimum)
- Corrupted file — try re-exporting your PDF or converting to plain text
- Provider issue — transient errors happen; create a new job with the same data
Training is taking longer than expected
Cloud models (OpenAI, Gemini) occasionally queue during high demand. If it's been over 2 hours, try creating a new job. GPU models (Qwen) should always complete within 10 minutes.
Model responses don't match my data
- Add more data — fine-tuning works better with more examples
- Be more specific in your use-case description
- Try a different base model — some models pick up certain patterns better than others