Instructions to use litert-community/squeezenet1_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/squeezenet1_1 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
Restore previous model card
Browse files
README.md
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library_name: litert
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tags:
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- litert
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- tflite
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- vision
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- image-classification
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datasets:
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- imagenet-1k
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# squeezenet1_1
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LiteRT TFLite conversion of the TorchVision `squeezenet1_1` model.
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## Files
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- `squeezenet1_1.tflite`
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- `squeezenet1_1_dynamic_wi8_afp32.tflite`
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## Notes
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These artifacts were compiled with the LiteRT GPU compatibility profile and validated with LiteRT Python GPU execution.
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library_name: litert
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tags:
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- vision
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- image-classification
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datasets:
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- imagenet-1k
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