---
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)
```