README.md

---
language:
- en
metrics:
- f1
---
# Interest extraction
  Extracts the interests from a question-answer pair.
### Model input
> summarize: [QUESTION]\
> [ANSWER]
### Example
> summarize: What do you like to do in the weekend?\
  I like to spend my free time reading, playing video games, and going on walks.

### Output
> reading, video games, walking

### How to use in code
```{python}
import nltk
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("njvdnbus/Interest_extraction")
model = AutoModelForSeq2SeqLM.from_pretrained("njvdnbus/Interest_extraction")

def use_model(text):
    inputs = ["summarize: " + text]
    inputs = tokenizer(inputs, truncation=True, return_tensors="pt")
    output = model.generate(**inputs, num_beams=1, do_sample=True, min_length=1, max_length=64)
    decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True)[0]
    predicted_interests = nltk.sent_tokenize(decoded_output.strip())[0]
    return predicted_interests

text= '''What other hobbies do you have?
When I have time I like to cook for my family. Most often this only happens in the weekends.'''
print(use_model(text))
```

> cooking