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Sentiment Classification in Polish
import numpy as np
from transformers import AutoTokenizer, AutoModelForSequenceClassification
id2label = {0: "negative", 1: "neutral", 2: "positive"}
tokenizer = AutoTokenizer.from_pretrained("Voicelab/herbert-base-cased-sentiment")
model = AutoModelForSequenceClassification.from_pretrained("Voicelab/herbert-base-cased-sentiment")
input = ["Ale fajnie, spadł dzisiaj śnieg! Ulepimy dziś bałwana?"]
encoding = tokenizer(
input,
add_special_tokens=True,
return_token_type_ids=True,
truncation=True,
padding='max_length',
return_attention_mask=True,
return_tensors='pt',
)
output = model(**encoding).logits.to("cpu").detach().numpy()
prediction = id2label[np.argmax(output)]
print(input, "--->", prediction)
Predicted output:
['Ale fajnie, spadł dzisiaj śnieg! Ulepimy dziś bałwana?'] ---> positive
Overview
- Language model: allegro/herbert-base-cased
- Language: pl
- Training data: Reviews + own data
- Blog post: Sentiment analysis - COVID-19 – the source of the heated discussion
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