Instructions to use litert-community/efficientnet_v2_m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/efficientnet_v2_m with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Adjusted metrics according to CPU evaluation
Browse files
README.md
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metrics:
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- name: Top 1 Accuracy (Full Precision)
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type: accuracy
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value: 0.
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- name: Top 5 Accuracy (Full Precision)
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type: accuracy
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value: 0.
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- name: Top 1 Accuracy (Dynamic Quantized wi8 afp32)
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type: accuracy
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value: 0.
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- name: Top 5 Accuracy (Dynamic Quantized wi8 afp32)
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type: accuracy
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value: 0.
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---
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# EfficientNet V2 M
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metrics:
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- name: Top 1 Accuracy (Full Precision)
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type: accuracy
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value: 0.8512
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- name: Top 5 Accuracy (Full Precision)
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type: accuracy
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value: 0.9716
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- name: Top 1 Accuracy (Dynamic Quantized wi8 afp32)
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type: accuracy
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value: 0.7208
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- name: Top 5 Accuracy (Dynamic Quantized wi8 afp32)
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type: accuracy
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value: 0.8613
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---
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# EfficientNet V2 M
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