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Update model card

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+ ---
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+ library_name: lucid
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+ license: apache-2.0
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+ tags:
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+ - image-classification
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+ - xception
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+ - lucid
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+ datasets:
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+ - imagenet-1k
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+ pipeline_tag: image-classification
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+ model-index:
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+ - name: xception
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+ results:
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+ - task: { type: image-classification }
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+ dataset: { name: ImageNet-1k, type: imagenet-1k }
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+ metrics:
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+ - { type: acc@1, value: 79.0 }
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+ ---
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+
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+ # Xception
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+
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+ > Chollet, 2017 — *Xception: Deep Learning with Depthwise Separable Convolutions* (arXiv:1610.02357)
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+
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+ [Lucid](https://github.com/ChanLumerico/lucid) port of `timm/legacy_xception.tf_in1k`,
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+ converted to Lucid-native safetensors.
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+
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+ ## Available weights
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+
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+ | Tag | acc@1 | acc@5 | Params | GFLOPs | Size | Source |
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+ |---|---|---|---|---|---|---|
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+ | `TF_IN1K` *(default)* | 79.0 | — | 22.9M | — | 87.42 MB | timm |
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+
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+ ## Usage
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+
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+ ```python
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+ import lucid.models as models
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+ from lucid.models.vision.resnet import XceptionWeights
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+
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+ # default tag
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+ model = models.xception_cls(pretrained=True)
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+
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+ # explicit tag (enum or string)
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+ model = models.xception_cls(weights=XceptionWeights.TF_IN1K)
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+ model = models.xception_cls(pretrained="TF_IN1K")
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+
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+ # preprocessing travels with the weights
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+ weights = XceptionWeights.TF_IN1K
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+ preprocess = weights.transforms()
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+ logits = model(preprocess(image)[None]).logits
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+ ```
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+
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+ ## Conversion
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+
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+ Converted from `timm/legacy_xception.tf_in1k` via
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+ `python -m tools.convert_weights xception --tag TF_IN1K`.
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+ Key mapping + numerical parity verified against the source.
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+
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+ ## License
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+
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+ `apache-2.0` — inherited from the original weights.
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+
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+ ## Citation
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+
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+ ```
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+ @inproceedings{chollet2017xception,
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+ title={Xception: Deep Learning with Depthwise Separable Convolutions},
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+ author={Chollet, Fran\c{c}ois},
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+ booktitle={CVPR}, year={2017}
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+ }
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+ ```