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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QE3") model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QE3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from NLP-EXP/QE3: direct link, hf CLI and curl.
- Browser
- Download file 215 Bytes
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https://huggingface.co/NLP-EXP/QE3/resolve/main/README.md
- Command line
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hf download hf://NLP-EXP/QE3/README.md
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curl -L -o README.md https://huggingface.co/NLP-EXP/QE3/resolve/main/README.md
215 Bytes
metadata
language:
- ar
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).