# Dataset Inference Run ML model inference on a FiftyOne dataset using Zoo models or your own. Supports detection, classification, segmentation, and embeddings. ## Install ```bash curl -sL skil.sh | sh -s -- voxel51/fiftyone-skills ``` When prompted, select **fiftyone-dataset-inference** from the menu. ## Requirements - [FiftyOne](https://docs.voxel51.com/getting_started/install.html) - [FiftyOne MCP Server](https://github.com/voxel51/fiftyone-mcp-server) (optional, recommended for operator-based inference) ## Usage Load a dataset in FiftyOne, then ask your AI assistant: ```default "Run YOLO object detection on my dataset" "Compute CLIP embeddings for all images" "Apply a segmentation model and store results in a new field" ``` The skill discovers available models dynamically, confirms the model and output field with you, then runs inference. ## Example ```python import fiftyone as fo import fiftyone.zoo as foz dataset = foz.load_zoo_dataset("quickstart") ``` Then ask your assistant: ```default "Run object detection on the quickstart dataset using a YOLO model" ``` ## See also - [Model Zoo docs](https://docs.voxel51.com/model_zoo/index.html) - [Applying models docs](https://docs.voxel51.com/user_guide/model_zoo/models.html)