Image Classification
Transformers
vision
Inference Endpoints
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@@ -19,6 +19,10 @@ This model was trained on the datasets: nih-pc-chex-mimic_ch-google-openi-rsna a
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  Here is how to use this model to classify an image of xray:
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  ```python
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  import urllib.request
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  Here is how to use this model to classify an image of xray:
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+ Note: Each pretrained model has 18 outputs. The `all` model has every output trained. However, for the other weights some targets are not trained and will predict randomly becuase they do not exist in the training dataset. The only valid outputs are listed in the field `{dataset}.pathologies` on the dataset that corresponds to the weights.
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+ Benchmarks of the modes are here: [BENCHMARKS.md](https://github.com/mlmed/torchxrayvision/blob/master/BENCHMARKS.md)
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  ```python
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  import urllib.request
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