| schema_version: 1 |
| id: EIDORA/AlexNet_IN1k |
| name: AlexNet_IN1k |
| version: 1.0.0 |
| model_family: AlexNet |
| backend: onnx |
| runtime: |
| adapter: onnx_image |
| execution_provider: CPUExecutionProvider |
| model_path: model.onnx |
| input_names: |
| - pixel_values |
| output_name: embedding |
| onnxruntime: |
| opset: 17 |
| tested_versions: '>=1.17,<2' |
| artifact: |
| path: model.onnx |
| sha256: 3e1277374f9da12a0c92084e19003dd541a792fccd5b4c0fd2bc4bfa54b28cc6 |
| package_size_bytes: 228020495 |
| inputs: |
| - id: image |
| modality: image |
| label: Images |
| required: true |
| source_kind: media_source |
| requirements: |
| color_space: RGB |
| layout: NCHW |
| width: 224 |
| height: 224 |
| preprocess: |
| image: |
| resize: |
| mode: resize_shorter_edge_then_center_crop |
| resize_size: 256 |
| crop_width: 224 |
| crop_height: 224 |
| interpolation: bilinear |
| source: TorchVision AlexNet_Weights.IMAGENET1K_V1.transforms |
| rescale: 1/255 |
| normalize: |
| mean: |
| - 0.485 |
| - 0.456 |
| - 0.406 |
| std: |
| - 0.229 |
| - 0.224 |
| - 0.225 |
| inside_onnx: true |
| embedding: |
| dimensions: 4096 |
| feature_type: embedding |
| pooling: fc_head |
| normalized: true |
| similarity: cosine |
| output_name: embedding |
| dtype: float32 |
| shape: |
| - batch |
| - 4096 |
| display: |
| summary: 'Light: classic ImageNet visual embeddings for fast first-pass grouping |
| on laptops.' |
| compute_tier: light |
| modality_labels: |
| - image |
| recommended_batch_size: 8 |
| validation: |
| fixtures: |
| - id: image_tensor_001 |
| input_shape: |
| - 1 |
| - 3 |
| - 224 |
| - 224 |
| expected_shape: |
| - 1 |
| - 4096 |
| seed: 17 |
| checks: |
| load_with: onnxruntime |
| execution_provider: CPUExecutionProvider |
| output_dtype: float32 |
| finite: true |
| normalized_l2_range: |
| - 0.99 |
| - 1.01 |
| provenance: |
| base_model: torchvision/alexnet-imagenet1k-v1 |
| source_repository: https://pytorch.org/vision/stable/models/generated/torchvision.models.alexnet.html |
| original_model_name: AlexNet ImageNet |
| original_model_url: https://proceedings.neurips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html |
| authors: |
| - Alex Krizhevsky |
| - Ilya Sutskever |
| - Geoffrey E. Hinton |
| paper_title: ImageNet Classification with Deep Convolutional Neural Networks |
| paper_url: https://proceedings.neurips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html |
| upstream_license: BSD-3-Clause for TorchVision code; ImageNet-trained weights distributed |
| by PyTorch under their documented model terms. |
| training_data: ImageNet-1K supervised classification data. |
| citation: "@inproceedings{krizhevsky2012imagenet,\n title={ImageNet Classification\ |
| \ with Deep Convolutional Neural Networks},\n author={Krizhevsky, Alex and Sutskever,\ |
| \ Ilya and Hinton, Geoffrey E.},\n booktitle={Advances in Neural Information\ |
| \ Processing Systems},\n year={2012}\n}\n" |
| conversion_note: EIDORA produced this ONNX conversion and is not the original model |
| creator. |
| export_date: '2026-07-10' |
| exporter_version: eidora-onnx-exporter 0.1.0 |
| model_card: |
| best_for: |
| - Fast baseline visual grouping. |
| - Small or exploratory image projects on ordinary laptops. |
| - Regression testing the EIDORA ONNX package pipeline. |
| not_ideal_for: |
| - Fine-grained visual similarity where modern self-supervised models perform better. |
| - Text, video, or audio inputs. |
| - Production-quality semantic image retrieval when a stronger model is acceptable. |
| limitations: AlexNet is an older supervised ImageNet model. It is useful as a lightweight |
| baseline, but modern CLIP, DINOv2, SigLIP, or domain-specific models will usually |
| produce stronger semantic similarity. |
| license: |
| id: bsd-3-clause |
| attribution: Converted to ONNX for EIDORA from the TorchVision AlexNet ImageNet |
| weights. |
| huggingface: |
| org: eidora |
| repo_name: alexnet_imagenet1k_4096 |
| pipeline_tag: feature-extraction |
| tags: |
| - eidora |
| - eidora-model-zoo |
| - onnx |
| - onnxruntime |
| - embeddings |
| - image |
| - alexnet |
| - imagenet |
| - compute:light |
| - modality:image |
| datasets: |
| - imagenet-1k |
| metrics: |
| - cosine-similarity |
|
|
