Create README.md

README.md

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+---
+language: en
+datasets:
+- FoodBase
+license: mit
+---
+# FoiodBaseBERT
+
+## Model description
+
+**FoodBaseBERT** is a fine-tuned BERT model that is ready to use for **Named Entity Recognition** of Food entities. It has been trained to recognize one entity: food (FOOD).
+
+Specifically, this model is a *bert-base-cased* model that was fine-tuned on the [FoodBase NER](https://academic.oup.com/database/article/doi/10.1093/database/baz121/5611291) dataset. 
+
+If you'd like to use a larger BERT-large model fine-tuned on the same dataset, a [**bert-large-NER**](https://huggingface.co/dslim/bert-large-NER/) version is also available. 
+
+
+## Intended uses
+
+#### How to use
+
+You can use this model with Transformers *pipeline* for NER.
+
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("Dizex/FoodBaseBERT")
+model = AutoModelForTokenClassification.from_pretrained("Dizex/FoodBaseBERT")
+
+pipe = pipeline("ner", model=model, tokenizer=tokenizer)
+example = "Today's meal: Fresh olive poké bowl topped with chia seeds. Very delicious!"
+
+ner_entity_results = pipe(example)
+print(ner_entity_results)
+```