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author | Laurent Mazare <laurent.mazare@gmail.com> | 2024-01-12 09:59:29 +0100 |
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committer | GitHub <noreply@github.com> | 2024-01-12 09:59:29 +0100 |
commit | 8e06bfb4fd33f1229a03abee20cc1c07198408b5 (patch) | |
tree | 89ea4cf4264e71f3247ab85451460e7a99efc7ac /candle-examples | |
parent | 6242276c0970db6e5805feed4c2ef3b0bf2ba413 (diff) | |
download | candle-8e06bfb4fd33f1229a03abee20cc1c07198408b5.tar.gz candle-8e06bfb4fd33f1229a03abee20cc1c07198408b5.tar.bz2 candle-8e06bfb4fd33f1229a03abee20cc1c07198408b5.zip |
Mention VGG in the readme. (#1573)
Diffstat (limited to 'candle-examples')
-rw-r--r-- | candle-examples/examples/repvgg/README.md | 6 |
1 files changed, 4 insertions, 2 deletions
diff --git a/candle-examples/examples/repvgg/README.md b/candle-examples/examples/repvgg/README.md index 2cb807c1..d24bcd6d 100644 --- a/candle-examples/examples/repvgg/README.md +++ b/candle-examples/examples/repvgg/README.md @@ -1,7 +1,9 @@ # candle-repvgg -A candle implementation of inference using a pre-trained [repvgg](https://arxiv.org/abs/2101.03697). -This uses a classification head trained on the ImageNet dataset and returns the +[RepVGG: Making VGG-style ConvNets Great Again](https://arxiv.org/abs/2101.03697). + +This candle implementation uses a pre-trained RepVGG network for inference. The +classification head has been trained on the ImageNet dataset and returns the probabilities for the top-5 classes. ## Running an example |