> This page is for version 0.5.0. > For other versions, use one of these documentation indexes: > - Latest (default): https://docs.nvidia.com/nemo-helix/latest/llms.txt > - 0.8.0: https://docs.nvidia.com/nemo-helix/v0.8.0/llms.txt > - 0.7.1: https://docs.nvidia.com/nemo-helix/v0.7.1/llms.txt > - 0.7.0: https://docs.nvidia.com/nemo-helix/v0.7.0/llms.txt > - 0.6.0: https://docs.nvidia.com/nemo-helix/v0.6.0/llms.txt > - 0.5.1: https://docs.nvidia.com/nemo-helix/v0.5.1/llms.txt > - 0.5.0: https://docs.nvidia.com/nemo-helix/v0.5.0/llms.txt > - 0.4.0: https://docs.nvidia.com/nemo-helix/v0.4.0/llms.txt > - 0.3.0: https://docs.nvidia.com/nemo-helix/v0.3.0/llms.txt > - 0.2.0: https://docs.nvidia.com/nemo-helix/v0.2.0/llms.txt > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nemo-helix/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo-helix/_mcp/server. # NeMo Studio Custom Models > Fine-tune models from NeMo Studio, and track customization jobs. Use **Models > Fine-tune** in the NeMo Studio workspace sidebar to open the Custom Models list, start Customizer jobs, and track their progress for the selected workspace. > **Note** > > Custom Models is enabled by default. An administrator can disable it by setting `studio.feature_flags.customizer_enabled: false` in the platform configuration and restarting Studio, which removes the **Custom Models** navigation entry and hides Customizer jobs from the general **Jobs** list. For customization concepts, supported models, and the underlying CLI and API workflow, see [Customization Concepts](/documentation/customizer-reference/customization-concepts). ## Start a Customization Job Select **Customize a Model** from the Custom Models list, or open a base model's details panel and select **Customize this Model**. Both open **Fine-tune a Model**, a single form with the following sections, shown as they apply to your selections: | Section | What you configure | | ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Training Backend | **Automodel** (multi-GPU), **Unsloth** (single-GPU, 4-bit quantized), or **RL**. | | Model | Base model, output model name, and description. | | Training Method | For Automodel and Unsloth: fine-tuning type (**LoRA**, **LoRA (Merged)**, or **Full Weights**), plus, for Automodel, training type (**SFT** or **Distillation**, with a teacher model field for distillation). For RL: **DPO** or **GRPO**. | | Reward Environment | Shown for GRPO jobs. Selects the reward environment used during training. | | Dataset | The training fileset, selected from filesets available in the workspace. | | Parameters | General hyperparameters, or GRPO-specific parameters when the training method is GRPO. | | LoRA Parameters | Shown when the training method uses a LoRA or LoRA-merged finetuning type. | | DPO Parameters | Shown for RL jobs using DPO. | | Compute Resources | GPU and node allocation for the job. | Several sections include an advanced JSON field for power-user overrides — for example raw parallelism or backend-specific keyword arguments — alongside the structured form fields. Use these only when a setting isn't exposed elsewhere in the form. Select **Start Fine-Tuning** to create the job. Studio confirms with a toast and navigates to the new job's detail page. Model eligibility for fine-tuning depends on the selected base model; **Customize this Model** is disabled for models that have no fileset to fine-tune from. ### Clone an Existing Job From a job's detail page, open the actions menu (**⋯**) and select **Clone** to open **Fine-tune a Model** pre-filled with that job's settings. Adjust any fields before submitting to start a new job. ## Custom Models List The Custom Models list shows fine-tuned models created in the current workspace. Select a row to open the model details side panel, which includes **Model Details** and **Chat Playground** tabs, a **Customize this Model** action, an **Evaluate this Model** action, and a **View Intake Traces** link when intake is enabled. ## Customization Job Details Select a job to open its detail page, which shows the job name, status badge, and metadata such as training type, base model, and creation date. | Tab | Shows | | -------------------- | ------------------------------------------------------------------------------- | | Overview | Training progress, run configuration, and the source dataset's fileset details. | | Logs | Job execution logs. | | Chat with your Model | A chat playground against the resulting model, shown once the job completes. | The Overview tab's training progress panel differs by training method: | Training method | Panel | Shows | | ---------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | | SFT, distillation, DPO | Training Loss | Train and validation loss per step, plus loss and progress stat tiles. | | GRPO | Reward | Training and validation reward per step (loss isn't meaningful for GRPO's policy-gradient objective), plus reward and progress stat tiles. | | GRPO | Training Health | Collapsed by default. Diagnostic charts from NeMo RL, such as KL divergence and clip fraction, that can flag a run diverging before reward does. | Below the training panel, **Run Configuration** summarizes the customization ID, output model, base model, and other run metadata, with a **View Job Configuration** action that opens the full job spec. From the detail page header, select **Evaluate** to start an evaluation against the resulting model once the job is launchable, or open the actions menu (**⋯**) for **Clone** and, while the job is active or pending, **Cancel Job**. ## Related Topics * [Customization Concepts](/documentation/customizer-reference/customization-concepts) * [Create a Customization Job](/documentation/customizer-reference/manage-customization-jobs/create-a-customization-job) * [Customization Job Reference](/documentation/customizer-reference/manage-customization-jobs/customization-job-reference) * [Experiments](/documentation/evaluate-models/experiments)