Update README.md

README.md

@@ -7,6 +7,7 @@ tags:
 - summarization
 datasets:
 - ml6team/cnn_dailymail_nl
+
 ---
 
 # mbart-large-cc25-cnn-dailymail-nl
@@ -21,26 +22,31 @@ It's meant for summarizing Dutch news articles.
 
 ```python
 import transformers
-undisputed_best_model = transformers.MBartForConditionalGeneration.from_pretrained('ml6team/mbart-large-cc25-cnn-dailymail-nl')
-tokenizer = transformers.MBartTokenizer.from_pretrained('facebook/mbart-large-cc25')
+
+undisputed_best_model = transformers.MBartForConditionalGeneration.from_pretrained(
+    "ml6team/mbart-large-cc25-cnn-dailymail-nl"
+)
+tokenizer = transformers.MBartTokenizer.from_pretrained("facebook/mbart-large-cc25")
 summarization_pipeline = transformers.pipeline(
-    task='summarization',
+    task="summarization",
     model=undisputed_best_model,
     tokenizer=tokenizer,
 )
-summ_pipeline_mbart.model.config.decoder_start_token_id=tokenizer.lang_code_to_id["nl_XX"]
-
-article = 'Kan je dit even samenvatten alsjeblief.'  # Dutch
-summ_pipeline_mbart(
-        article,
-        do_sample=True,
-        top_p=0.75,
-        top_k=50,
-        # num_beams=4,
-        min_length=50,
-        early_stopping=True,
-        truncation=True,
-    )[0]['summary_text']
+summarization_pipeline.model.config.decoder_start_token_id = tokenizer.lang_code_to_id[
+    "nl_XX"
+]
+
+article = "Kan je dit even samenvatten alsjeblief."  # Dutch
+summarization_pipeline(
+    article,
+    do_sample=True,
+    top_p=0.75,
+    top_k=50,
+    # num_beams=4,
+    min_length=50,
+    early_stopping=True,
+    truncation=True,
+)[0]["summary_text"]
 ```
 
 ## Training data