model-index

import os from pathlib import Path from modelindex.models import ModelIndex # 1. Create a dummy model-index.yml file for demonstration model_index_content = ''' Models: - Name: MyAwesomeModelV1 Metadata: Task: Image Classification Dataset: CIFAR-10 Metrics: Accuracy: 0.92 Paper: https://arxiv.org/abs/2301.00001 Code: https://github.com/myuser/myawesomemodel Weights: https://example.com/weights.pth License: MIT - Name: MyAwesomeModelV2 Metadata: Task: Image Classification Dataset: CIFAR-10 Metrics: Accuracy: 0.94 Paper: https://arxiv.org/abs/2302.00002 Code: https://github.com/myuser/myawesomemodel Weights: https://example.com/weights_v2.pth License: Apache-2.0 ''' index_file_path = "model-index.yml" Path(index_file_path).write_text(model_index_content) print(f"Created dummy {index_file_path}") try: # 2. Load the model index from the YAML file # Note: The exact loading method might vary; .load_from_file() is a common pattern. # The library's core is parsing these files. model_index = ModelIndex.load_from_file(index_file_path) print(f"\nSuccessfully loaded {len(model_index.models)} model(s).") # 3. Access data from the loaded index for i, model in enumerate(model_index.models): print(f"\n--- Model {i+1} ---") print(f"Name: {model.name}") print(f"Task: {model.metadata['Task']}") print(f"Accuracy: {model.metadata['Metrics']['Accuracy']}") print(f"Paper: {model.metadata['Paper']}") except Exception as e: print(f"An error occurred during loading or processing: {e}") finally: # Clean up the dummy file if Path(index_file_path).exists(): os.remove(index_file_path) print(f"\nCleaned up {index_file_path}")