voyager-list-models

List Available Models

List and search models in the Voyager SDK model zoo for Axelera AI hardware

Important Context

Do not call a model deployable or validated until SDK evidence and runtime artifacts show that status.

Instructions

List models based on the specified criteria: $ARGUMENTS

Step 0: Data Source & Environment Selection

{{INCLUDE common/voyager-sdk-setup.md}}

Step 0.5: Axelera Voyager Project & Task Integration

{{INCLUDE common/voyager-task-integration.md}}

Step 1: List All Models

# Show all available models
./deploy.py --help

# Or use make (help is the default target; prints per-model help)
make help

Classify each result as:

• listed: YAML or deploy help entry exists
• payload-present: compiled payload exists under build/<model>/
• downloadable: axdownloadmodel <model> succeeds and payload exists
• metis-validated: inference.py ran on visible Metis hardware and produced output

Step 2: Search by Task Type

Search models by their primary task:

Object Detection:

# YOLO models
ls ax_models/zoo/yolo/object_detection/

# Oriented bounding boxes (OBB)
ls ax_models/zoo/yolo/obb_detection/

# SSD models
ls ax_models/zoo/tensorflow/object_detection/

# RetinaFace (face detection)
ls ax_models/zoo/torch/ | grep -i retinaface

Classification:

# TorchVision classifiers
ls ax_models/zoo/torchvision/classification/

# Timm models
ls ax_models/zoo/timm/

Segmentation:

# Instance segmentation (YOLO-based)
ls ax_models/zoo/yolo/instance_segmentation/

# Semantic segmentation
ls ax_models/zoo/mmlab/mmseg/
ls ax_models/zoo/yolo/semantic_segmentation/

Pose Estimation:

# Pose models (YOLO-based keypoint detection)
ls ax_models/zoo/yolo/keypoint_detection/

Depth Estimation:

ls ax_models/zoo/torch/ | grep -i depth

LLM/Language Models:

ls ax_models/zoo/llm/
ls ax_models/llm/

Step 3: Search by Framework