Instructions to use Kalloniatis/Humor-Recognition_Greek-twhin-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kalloniatis/Humor-Recognition_Greek-twhin-bert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kalloniatis/Humor-Recognition_Greek-twhin-bert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kalloniatis/Humor-Recognition_Greek-twhin-bert-large") model = AutoModelForSequenceClassification.from_pretrained("Kalloniatis/Humor-Recognition_Greek-twhin-bert-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
The model is based on TwHIN-BERT large ("Twitter/twhin-bert-large") fine-tuned for Humor Recognition in Greek language.
TwHIN-BERT is a large pre-trained language model for Multilingual Tweets that is trained on 7 billion Tweets from over 100 distinct languages
Model Details
The model was pre-trained over 10 epochs on Greek Humorous Dataset
Pre-processing details
The text needs to be pre-processed by removing all greek diacritics and punctuation and converting all letters to lowercase
Load Pretrained Model
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("kallantis/Humor-Recognition-Greek-twhin-bert-large")
model = AutoModelForSequenceClassification.from_pretrained("kallantis/Humor-Recognition-Greek-twhin-bert-large", num_labels=2, ignore_mismatched_sizes=True)
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