Instructions to use NLP-EXP/QSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-EXP/QSR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QSR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QSR") model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QSR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from NLP-EXP/QSR: direct link, hf CLI and curl.
- Browser
- Download file 231 Bytes
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https://huggingface.co/NLP-EXP/QSR/resolve/main/README.md
- Command line
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hf download hf://NLP-EXP/QSR/README.md
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curl -L -o README.md https://huggingface.co/NLP-EXP/QSR/resolve/main/README.md
231 Bytes
metadata
language:
- ar
The QARiB-Sentiment-Reviews (QSR) Model is a QARiB language model that was further pre-trained for 300,000 training steps and roughly 26 epochs using sentiment review dataset (involves over 751,000 reviews).