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:
- f7fc8b919a97ffd963eec98fc547c88d38a5ba7885b78befe77bf825d837588e
- Size of remote file:
- 2.86 kB
- SHA256:
- f07bf60fbd6be7cd58ce12b29f8ef1d567b807364f7d4e81685e879b7359c783
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