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-finetune"
+)
+tokenizer = transformers.MBartTokenizer.from_pretrained("facebook/mbart-large-cc25")
+summarization_pipeline = transformers.pipeline(
+    task="summarization",
+    model=undisputed_best_model,
+    tokenizer=tokenizer,
+)
+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
+Finetuned [mbart](https://huggingface.co/facebook/mbart-large-cc25) with [this dataset](https://huggingface.co/datasets/ml6team/cnn_dailymail_nl) and another smaller dataset that we can't open source because we scraped it from the internet. For more information check out our blog post [here](https://blog.ml6.eu/).