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README.md

@@ -3,7 +3,7 @@
 ---
 license: mit
 language:
-- fr
+- multilingual
 tags:
 - zero-shot-classification
 - text-classification
@@ -14,7 +14,7 @@ metrics:
 ---
 # xlm-roberta-large-french-party-cap-v3
 ## Model description
-An `xlm-roberta-large` model finetuned on french training data containing texts of the `party` domain labelled with [major topic codes](https://www.comparativeagendas.net/pages/master-codebook) from the [Comparative Agendas Project](https://www.comparativeagendas.net/).
+An `xlm-roberta-large` model finetuned on multilingual training data containing texts of the `party` domain labelled with [major topic codes](https://www.comparativeagendas.net/pages/master-codebook) from the [Comparative Agendas Project](https://www.comparativeagendas.net/).
 
 ## How to use the model
 #### Loading and tokenizing input data
@@ -47,8 +47,10 @@ dataset = hg_data.map(tokenize_dataset, batched=True, remove_columns=hg_data.col
 #### Inference using the Trainer class
 ```python
 model = AutoModelForSequenceClassification.from_pretrained('poltextlab/xlm-roberta-large-french-party-cap-v3',
-                                                           num_labels=21,
-                                                           problem_type="multi_label_classification")                                                           )
+                                                           num_labels=num_labels,
+                                                           problem_type="multi_label_classification",
+                                                           ignore_mismatched_sizes=True
+                                                           )
 
 training_args = TrainingArguments(
     output_dir='.',