- TRAINED
- MONITOR
- RECOVERY
- HUMAN
Short answer
How can I fine tune a model using my AI?
You upload your training data and tell your agent to start a fine-tuning job. Your agent then manages the training on dedicated hardware and tracks progress through checkpoints.
The training outcomes
What you get from training
These are the results of your fine-tuning requests.
TRAINED
Specialized model
The training finishes and you have a model tuned for your specific niche tasks. It understands your unique data patterns.
MONITOR
Live status updates
Your agent tracks the training progress. You can see if a job is still running or if it has completed.
RECOVERY
Checkpoint access
The AI pulls specific versions of the model from different stages of the run. This lets you inspect the training history.
HUMAN
Manual evaluation
You must review the model's performance yourself. The AI can't determine if the model's output is actually useful for your specific needs.
The workflow
What your AI does when the request arrives.
Your agent acts as the manager for the entire training lifecycle.
Prepare data
Your agent sends your training files to the Together AI environment.
upload_fileStart training
The AI triggers the fine-tuning process on dedicated hardware using your data.
create_fine_tuneTrack jobs
Your agent monitors active training runs to check their current status.
list_fine_tunesget_fine_tuneRetrieve checkpoints
The AI looks through the different stages of the training to find specific model versions.
list_fine_tune_checkpoints
Try it
Copy these to start.
Use these prompts to kick off your training tasks.
Starting points
Swap out the file names and model IDs for your own.
Together AI Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Together AI capabilities are ready to use.
{
"mcpServers": {
"together-ai-alternative-mcp": {
"url": "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"
}
}
}Upload my training data from training_set.json and start a fine-tune job.
Show me all the fine-tunes I have currently running.
Check the status of the fine-tune with ID model_123.
List the checkpoints available for my latest fine-tune job.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Together AI once, then ask.
Link your account once. Your credentials stay encrypted, and you can immediately start managing models through your AI client.
Connect Together AI to your AIFAQ
How this task behaves
- 01
Can my AI delete my existing models?
No. The tools only allow for uploading, creating, listing, and getting model information.
- 02
Can the AI automatically decide when a model is finished training?
No. The AI reports the status, but you must decide when to stop or move to the next phase.
- 03
How does the AI handle large datasets?
The AI uses the upload tool to move your files to the Together AI environment before starting the job.
- 04
Can I see the progress of a training job?
Yes. Your agent can check the status of specific jobs or list all active fine-tunes.
- 05
Can the AI change my training parameters mid-run?
No. The tools are for initiating and monitoring jobs, not for modifying an active training process.
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