# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QSRT")
model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QSRT")Quick Links
The QARiB-Sentiment-Reviews-Tweets (QSRT) Model is the continuation of training from the last checkpoint of the QSR model for an additional 300k training steps (600k in total with QSR training steps). The QSRT model was trained for roughly 52 epochs using sentiment dataset contains both tweets and reviews (consists of 1,433,657 sentences).
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QSRT")