Instructions to use litert-community/efficientnet_b2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/efficientnet_b2 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
Commit History
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Card: declare base_model_relation: quantized (#4)
- Card: declare base_model_relation: quantized (8fe140f9ad3711ed70ac1b1dfa72fb97ce35ef24) Co-authored-by: Daisuke Majima (MLBoy) <mlboydaisuke@users.noreply.huggingface.co>453836c
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Card: revert base_model_relation line added earlier today (repo not authored by me)
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Card: base_model_relation: quantized (list under the base model's Quantizations)
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Replace dynamic-range int8 with weight-only int8 (#3)
- Replace dynamic-range int8 with weight-only int8 (243765d73402beb5f475eb951d21a13a7cbb489d) Co-authored-by: Majima <mlboydaisuke@users.noreply.huggingface.co>0ee1da6
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Upload efficientnet_b2_Google_Tensor_G5_apply_plugin.tflite with huggingface_hub
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Updated README.md (#2)
- Updated README.md (750783bc9351f117a66df8235a59398029fc565d) Co-authored-by: Akash Verma <akashvverma1995@users.noreply.huggingface.co>0fa8760
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Updated the README.md (#1)
- updated the README.md (c3fffbf22eff5df0d5c4588a291954aa875001e5) Co-authored-by: Akash Verma <akashvverma1995@users.noreply.huggingface.co>6be6c2b
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Upload README.md with huggingface_hub
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Upload README.md with huggingface_hub
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Upload README.md with huggingface_hub
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Initial model upload
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initial commit
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