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@@ -90,7 +90,8 @@ This is a fine-tuned GeoLM model for toponym detection task. The inputs are sent
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  To use this model, please refer to the code below.
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- * Option 1: Load weights to a BERT model (Same procedure as the demo on the right side panel)
 
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  ```import torch
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  from transformers import AutoModelForTokenClassification, AutoTokenizer
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  # Print predicted labels
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  print(predicted_labels)
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  ```
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- * Option 2: Load weights to a GeoLM model
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  To appear soon
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@@ -133,7 +134,8 @@ To appear soon
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  <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- GeoWebNews (Credit to Gritta et al.)
 
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  Download link: https://github.com/milangritta/Pragmatic-Guide-to-Geoparsing-Evaluation/blob/master/data/GWN.xml
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  ## Training Procedure
 
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  To use this model, please refer to the code below.
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+ * **Option 1:** Load weights to a BERT model (Same procedure as the demo on the right side panel)
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+
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  ```import torch
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  from transformers import AutoModelForTokenClassification, AutoTokenizer
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  # Print predicted labels
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  print(predicted_labels)
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  ```
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+ * **Option 2:** Load weights to a GeoLM model
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  To appear soon
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  <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+ **GeoWebNews** (Credit to [Gritta et al.](https://arxiv.org/pdf/1810.12368.pdf))
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  Download link: https://github.com/milangritta/Pragmatic-Guide-to-Geoparsing-Evaluation/blob/master/data/GWN.xml
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  ## Training Procedure