- RUNNING
- DEPLOYED
- MONITOR
- HUMAN
Short answer
How can I fine-tune models using my AI?
You tell your AI to start a training job using your datasets. It handles the execution on Replicate and monitors the progress until the model is ready. You'll see the results of these training runs through the following breakdown.
Training outcomes
What you get from training
These are the results of your training requests.
RUNNING
Active training jobs
The AI starts the process and keeps an eye on the logs. You get updates on whether the job is still working or if it failed.
DEPLOYED
Ready to use models
Once a job finishes, the AI creates a new model version. This makes your custom weights available for immediate use.
MONITOR
Real-time status
Your agent can check on any existing training run. You'll know exactly when a model is ready without checking a separate dashboard.
HUMAN
Dataset management
The AI cannot prepare or clean your training data. You must host your files in a place Replicate can reach before you ask the AI to start.
The workflow
What your AI does when you request training.
The AI manages the heavy lifting on Replicate so you can stay in your chat client.
Initiate training
The AI sends your training configuration and dataset location to Replicate to kick off a new job.
create_trainingTrack progress
The AI checks the current status of your training run to see if it's still active or completed.
get_trainingRegister model
When the training succeeds, the AI creates a new model version from the resulting weights.
create_modelVerify status
The AI checks the training details again to confirm everything finished correctly.
get_training
Try it
Copy these to start.
Use these prompts to begin your fine-tuning work.
Starting points
Swap out the dataset URLs and model names for your own specific files.
Replicate Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_ULeVbcRjoLCkIr9x93q2HML8VJd4AXmk4CWHHPso/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 — Replicate capabilities are ready to use.
{
"mcpServers": {
"replicate-extended-mcp": {
"url": "https://edge.vinkius.com/vk_preview_ULeVbcRjoLCkIr9x93q2HML8VJd4AXmk4CWHHPso/mcp"
}
}
}Start a new training session using the dataset at https://example.com/my-data.jsonl
Check the status of my training job to see if it is done.
Create a new model from the training run I just finished.
Get the status of the training job with ID training_12345.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Replicate once, then ask.
Link your Replicate account to Vinkius. Your credentials stay encrypted, and you can start managing models immediately.
Connect Replicate to your AIFAQ
How this task behaves
- 01
Can the AI clean my training data?
No. The AI can only start training once you provide a valid dataset URL. It cannot edit your files.
- 02
Can the AI delete my models?
No. This MCP only has tools to create training jobs and models. It cannot delete anything.
- 03
Can I see if a training job failed?
Yes. The AI can check the status of your training runs and report back if there was an error.
- 04
Does the AI handle my Replicate billing?
No. All costs are handled through your own Replicate account.
- 05
Can I stop a training session?
No. There is no tool available to cancel or stop a training job once it has started.
More questions about Replicate? The Connector page answers them. See everything the Replicate Connector can do
Connect Replicate to Claude, Cursor, ChatGPT & more
