# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QST")
model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QST")Quick Links
the QARiB-Sentiment-Tweets (QST) Model is a QARiB language model that was further pre-trained for 300K training steps and roughly 28 epochs using sentiment tweets dataset (contains over 682,000 tweets)
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QST")