v0.58.0
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.58.0 for changelog.
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README.md
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Contrastive Language-Image Pre-Training (CLIP) uses a ViT like transformer to get visual features and a causal language model to get the text features. Both the text and visual features can then be used for a variety of zero-shot learning tasks.
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This is based on the implementation of OpenAI-Clip found [here](https://github.com/openai/CLIP/).
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This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.
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For more device-specific assets and performance metrics, visit **[OpenAI-Clip on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/openai_clip)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [OpenAI-Clip on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| OpenAI-Clip | ONNX | float | Snapdragon® X2 Elite | 10.
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| OpenAI-Clip | ONNX | float | Snapdragon® X Elite | 22.
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| OpenAI-Clip | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 14.
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| OpenAI-Clip | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 26.
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| OpenAI-Clip | ONNX | float | Qualcomm® QCS8550 (Proxy) | 21.
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| OpenAI-Clip | ONNX | float | Qualcomm® QCS8450 | 26.
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| OpenAI-Clip | ONNX | float |
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| OpenAI-Clip | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 9.
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| OpenAI-Clip | ONNX | float |
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| OpenAI-Clip | ONNX | float | Qualcomm®
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| OpenAI-Clip | ONNX | float | Qualcomm®
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® X2 Elite | 9.
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® X Elite | 21.
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 14.
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 24.
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® QCS8275 | 59.
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 20.
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| OpenAI-Clip | QNN_DLC | float | Qualcomm®
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| OpenAI-Clip | QNN_DLC | float |
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| OpenAI-Clip | QNN_DLC | float | Qualcomm®
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| OpenAI-Clip | QNN_DLC | float |
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| OpenAI-Clip | QNN_DLC | float | Qualcomm®
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| OpenAI-Clip | QNN_DLC | float |
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| OpenAI-Clip | QNN_DLC | float | Qualcomm®
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| OpenAI-Clip | QNN_DLC | float |
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| OpenAI-Clip |
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| OpenAI-Clip |
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| OpenAI-Clip |
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| OpenAI-Clip | TFLITE | float |
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| OpenAI-Clip | TFLITE | float |
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| OpenAI-Clip | TFLITE | float | Qualcomm®
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| OpenAI-Clip | TFLITE | float | Qualcomm®
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| OpenAI-Clip | TFLITE | float | Qualcomm®
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| OpenAI-Clip | TFLITE | float |
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| OpenAI-Clip | TFLITE | float | Qualcomm®
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| OpenAI-Clip | TFLITE | float |
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| OpenAI-Clip | TFLITE | float | Qualcomm®
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| OpenAI-Clip | TFLITE | float |
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| OpenAI-Clip | TFLITE | float | Qualcomm®
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## License
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* The license for the original implementation of OpenAI-Clip can be found
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Contrastive Language-Image Pre-Training (CLIP) uses a ViT like transformer to get visual features and a causal language model to get the text features. Both the text and visual features can then be used for a variety of zero-shot learning tasks.
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This is based on the implementation of OpenAI-Clip found [here](https://github.com/openai/CLIP/).
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This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/openai_clip) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.58.0/openai_clip-onnx-float.zip)
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.58.0/openai_clip-qnn_dlc-float.zip)
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.58.0/openai_clip-tflite-float.zip)
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For more device-specific assets and performance metrics, visit **[OpenAI-Clip on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/openai_clip)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/openai_clip) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [OpenAI-Clip on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/openai_clip) for usage instructions.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| OpenAI-Clip | ONNX | float | Snapdragon® X2 Elite | 10.389 ms | 2 - 2 MB | NPU
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| OpenAI-Clip | ONNX | float | Snapdragon® X Elite | 22.087 ms | 295 - 295 MB | NPU
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| OpenAI-Clip | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 14.92 ms | 0 - 1105 MB | NPU
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| OpenAI-Clip | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 26.753 ms | 1 - 687 MB | NPU
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| OpenAI-Clip | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 21.325 ms | 0 - 323 MB | NPU
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| OpenAI-Clip | ONNX | float | Qualcomm® QCS8450 | 26.753 ms | 1 - 687 MB | NPU
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| OpenAI-Clip | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 30.849 ms | 0 - 4 MB | NPU
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| OpenAI-Clip | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 9.261 ms | 1 - 584 MB | NPU
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| OpenAI-Clip | ONNX | float | Snapdragon® 8 Elite Mobile | 11.631 ms | 0 - 869 MB | NPU
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| OpenAI-Clip | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 11.631 ms | 0 - 869 MB | NPU
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| OpenAI-Clip | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 22.087 ms | 295 - 295 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® X2 Elite | 9.645 ms | 1 - 1 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® X Elite | 21.391 ms | 1 - 1 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 14.547 ms | 0 - 770 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 24.245 ms | 0 - 608 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® QCS8275 | 59.346 ms | 1 - 569 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 20.411 ms | 1 - 579 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® SA8775P | 23.09 ms | 1 - 568 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® SA8650P | 23.09 ms | 1 - 568 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® SA8255P | 23.09 ms | 1 - 568 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® QCS8450 | 24.245 ms | 0 - 608 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 23.86 ms | 3 - 5 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 8.742 ms | 0 - 419 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® SA7255P | 59.346 ms | 1 - 569 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 11.321 ms | 0 - 586 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® SA8295P | 24.62 ms | 1 - 514 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 11.321 ms | 0 - 586 MB | NPU
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| OpenAI-Clip | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 21.391 ms | 1 - 1 MB | NPU
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| OpenAI-Clip | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 14.216 ms | 0 - 773 MB | NPU
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| OpenAI-Clip | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 24.231 ms | 0 - 618 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® QCS8275 | 59.398 ms | 0 - 565 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 20.306 ms | 0 - 3 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® SA8775P | 23.093 ms | 0 - 566 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® SA8650P | 23.093 ms | 0 - 566 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® SA8255P | 23.093 ms | 0 - 566 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® QCS8450 | 24.231 ms | 0 - 618 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 23.106 ms | 0 - 296 MB | NPU
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| OpenAI-Clip | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 8.745 ms | 0 - 434 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® SA7255P | 59.398 ms | 0 - 565 MB | NPU
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| OpenAI-Clip | TFLITE | float | Snapdragon® 8 Elite Mobile | 11.303 ms | 0 - 599 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® SA8295P | 24.52 ms | 0 - 517 MB | NPU
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| OpenAI-Clip | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 11.303 ms | 0 - 599 MB | NPU
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## License
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* The license for the original implementation of OpenAI-Clip can be found
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release_assets.json
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{
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"version": "0.
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"precisions": {
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"float": {
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"universal_assets": {
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"qairt": "2.45.0.260326154327",
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"litert": "1.4.4"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.
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},
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"qnn_dlc": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.
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},
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"onnx": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327",
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"onnx_runtime": "1.25.0"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.
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}
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}
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}
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{
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"version": "0.58.0",
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"precisions": {
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"float": {
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"universal_assets": {
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"qairt": "2.45.0.260326154327",
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"litert": "1.4.4"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.58.0/openai_clip-tflite-float.zip"
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},
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"qnn_dlc": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.58.0/openai_clip-qnn_dlc-float.zip"
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},
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"onnx": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327",
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"onnx_runtime": "1.25.0"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/openai_clip/releases/v0.58.0/openai_clip-onnx-float.zip"
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}
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}
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}
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