Create README.md

README.md

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+---
+language: 
+- nl
+tags:
+- mbart
+- bart
+- summarization
+datasets:
+- ml6team/cnn_dailymail_nl
+---
+
+# mbart-large-cc25-cnn-dailymail-nl
+
+## Model description
+Finetuned version of [mbart](https://huggingface.co/facebook/mbart-large-cc25). We also wrote a blog post about this model [here](https://blog.ml6.eu/)
+
+## Intended uses & limitations
+It's meant for summarizing Dutch news articles.
+
+#### How to use
+
+```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')
+summarization_pipeline = transformers.pipeline(
+    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']
+```
+
+## Training data
+Finetuned [mbart](https://huggingface.co/facebook/mbart-large-cc25) with [this dataset](https://huggingface.co/datasets/ml6team/cnn_dailymail_nl)