- A model for predicting the source of news articles
Usage:
import re
from transformers import pipeline
from html import unescape
from unicodedata import normalize
re_multispace = re.compile(r"\s+")
def normalize_text(text):
if text == None:
return None
text = text.strip()
text = text.replace("\n", " ")
text = text.replace("\t", " ")
text = text.replace("\r", " ")
text = re_multispace.sub(" ", text)
text = unescape(text)
text = normalize("NFKC", text)
return text
model = pipeline(task="text-classification",
model=f"hynky/Server", tokenizer="ufal/robeczech-base",
truncation=True, max_length=512,
top_k=5
)
def predict(article):
article = normalize_text(article)
predictions = model(article)
predict("Dnes v noci bude pršet.")
- Downloads last month
- 19
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.