Commit History
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Replace dynamic-range int8 with weight-only int8
Verified signatureSame change as efficientnet_b1 (merged earlier today), applied for consistency across the family: this repo's dynamic-range int8 is only mildly affected, but weight-only int8 is strictly closer to the float model at the same size reduction. Measured against the torch float reference on real photos plus fixed random tensors at native resolution: dynamic min logit correlation 0.971 (top-1 4/6) vs weight-only 1.000 (top-1 6/6). The replacement file is quantized directly from this repository's published float32 file (litert quantize, recipe weight_only_wi8_afp32), so the weights are identical. The model card is updated in the same commit: the metric entries for the removed dynamic file are dropped and a short quantized-variant note with the measured numbers is added.c9d5301
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Upload efficientnet_b6_Google_Tensor_G5_apply_plugin.tflite with huggingface_hub
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Updated README.md File (#2)
- Updated README.md File (5247c63abeb93ff920c76219ce0bc6f29ecd208c) Co-authored-by: Akash Verma <akashvverma1995@users.noreply.huggingface.co>a29d46b
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Update README: Add model card metadata, ImageNet-1k metrics, and LiteRT usage example (#1)
- Update README: Add model card metadata, ImageNet-1k metrics, and LiteRT usage example (5909a02cb59cc1ba1f7b211b859afae398681868) Co-authored-by: Akash Verma <akashvverma1995@users.noreply.huggingface.co>9e2bfa0
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Upload README.md with huggingface_hub
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Upload README.md with huggingface_hub
Verified signatureddf66b8 -
Upload README.md with huggingface_hub
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Initial model upload
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initial commit
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