Instructions to use NLP-EXP/QE3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-EXP/QE3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QE3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QE3") model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QE3") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QE3")
model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QE3")Quick Links
The QARiB-Emotion-300k (QE3) is a QARiB language model that was further pre-trained for 300k training steps and roughly 28 epochs using the emotion tweets dataset (roughly 1.2 million tweets).
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QE3")