README.md

---
language:
- it
pipeline_tag: question-answering
tags:
- Biomedical Language Modeling
library_name: Haystack
---

🤗 + 📚🩺🇮🇹  + ❓ =  **BioBIT_QA**

From this repository you can download the **BioBIT_QA** (Biomedical Bert for ITalian for Question Answering) checkpoint.

**BioBIT_QA** is built on top of [BioBIT](https://huggingface.co/IVN-RIN/bioBIT), fine-tuned on an Italian Neuropsychological Italian datasets.
More details will follow!


## Install libraries:

```
pip install farm-haystack[inference]
```


## Download model locally:

```
git clone https://huggingface.co/IVN-RIN/bioBIT_QA
```


## Run the code

```
# Import libraries
from haystack.nodes import FARMReader
from haystack.schema import Document

# Define the reader
reader = FARMReader(
    model_name_or_path="bioBIT_QA",
    return_no_answer=True
)

# Define context and question
context = '''
This is an example of context
'''
question = 'This is a question example, ok?'

# Wrap context in Document
docs = Document(
    content = context
)

# Predict answer
prediction = reader.predict(
    query = question,
    documents = [docs],
    top_k = 5
)

# Print the 5 first predicted answers
for i, ans in enumerate(prediction['answers']):
    print(f'Answer num {i+1}, with score {ans.score*100:.2f}%: "{ans.answer}"')
    
# Inferencing Samples: 100%|██████████| 1/1 [00:01<00:00,  1.14s/ Batches]
# Answer num 1, with score 97.91%: "Example answer 01"
# Answer num 2, with score 53.69%: "Example answer 02"
# Answer num 3, with score 0.03%: "Example answer 03"
# ...


```