Create a Fine-tuning Instance
Access Entry
On the base model details page you want to fine-tune, click the Fine-tune Instance button in the top right corner to navigate to the creation page.
Tip
Configuration Parameters
On the fine-tuning instance creation page, fill in the following configuration, then click Create Instance:
| Parameter | Description |
|---|---|
| Instance Name | Custom name; must not duplicate existing instances (e.g., qwen-medical-finetune) |
| Model ID | The model identifier on the platform; defaults to the currently selected base model |
| Region/Resource Config | Select GPU resources appropriate for the base model size (VRAM must accommodate the model and training gradients) |
| Runtime Framework | Select the fine-tuning framework: LLaMA-Factory or MS-Swift |
View Instance List
After creation, use the top navigation to open Model Training & Evaluation → Fine-tuning Instances to monitor instance startup progress and manage running fine-tuning tasks in real time. You can also view them centrally in Resource Management.
Using the Fine-tuning Framework
Once the instance is running, click the instance name to enter the fine-tuning framework interface:
- LLaMA-Factory: Provides the visual LlamaBoard interface — select dataset, configure LoRA parameters, start training, and view real-time loss curves and other training metrics.
- MS-Swift: Provides both command-line and web interface options, supporting more model types and quantized fine-tuning options.
Exporting the Fine-tuned Model
After training completes, merge and export the fine-tuned weights as a new independent model repository for subsequent inference deployment or evaluation.