Personalised opener
This model creates an opener based on a provided interest.
Model input
[INTEREST]
Example
dancing
Output
What's your favorite dance move to make people laugh or cry?
How to use in code
import nltk
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("njvdnbus/personalised_opener-t5-large")
model = AutoModelForSeq2SeqLM.from_pretrained("njvdnbus/personalised_opener-t5-large")
def use_model(text):
inputs = ["" + text]
inputs = tokenizer(inputs, truncation=True, return_tensors="pt")
output = model.generate(**inputs, num_beams=1, do_sample=True, min_length=10, max_length=256)
decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True)[0]
predicted_interests = nltk.sent_tokenize(decoded_output.strip())[0]
return predicted_interests
text= "tennis"
print(use_model(text))
Do you think tennis is the most exciting sport out there?
- Downloads last month
- 3
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.