Instructions to use Razan/QAIDeptModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Razan/QAIDeptModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Razan/QAIDeptModel")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Razan/QAIDeptModel") model = AutoModelForMaskedLM.from_pretrained("Razan/QAIDeptModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 552686f1f7ddbbbfad3481cf0ddf00e2692190cb791d367021bc0ea5bb4b533e
- Size of remote file:
- 541 MB
- SHA256:
- 822b794dd8c640f69ae98ad53297682da98311ba09edc0311cb04a503a103ed7
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