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@@ -19,7 +19,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # detr-resnet-50_fine_tuned_nls_chapbooks
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- This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the nls_chapbook_illustrations dataset.
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  ## Model description
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  ### Using in a transformer pipeline
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- The easiest way to use this model is via a [Transformers pipeline](https://huggingface.co/docs/transformers/main/en/pipeline_tutorial#vision-pipeline). To do this you should first load the model and feature extractor:
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  ```python
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  from transformers import AutoFeatureExtractor, AutoModelForObjectDetection
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  model = AutoModelForObjectDetection.from_pretrained("davanstrien/detr-resnet-50_fine_tuned_nls_chapbooks")
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  ```
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- Then you can create a pipeline for object detection using the model
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  ```python
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  from transformers import pipeline
 
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  # detr-resnet-50_fine_tuned_nls_chapbooks
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+ This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the `biglam/nls_chapbook_illustrations` dataset. This dataset contains images of chapbooks with bounding boxes for the illustrations contained on some of the pages.
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  ## Model description
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  ### Using in a transformer pipeline
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+ The easiest way to use this model is via a [Transformers pipeline](https://huggingface.co/docs/transformers/main/en/pipeline_tutorial#vision-pipeline). To do this, you should first load the model and feature extractor:
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  ```python
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  from transformers import AutoFeatureExtractor, AutoModelForObjectDetection
 
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  model = AutoModelForObjectDetection.from_pretrained("davanstrien/detr-resnet-50_fine_tuned_nls_chapbooks")
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  ```
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+ Then you can create a pipeline for object detection using the model.
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  ```python
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  from transformers import pipeline