Instructions to use Rehab-Hamdy/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rehab-Hamdy/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rehab-Hamdy/model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rehab-Hamdy/model") model = AutoModelForMaskedLM.from_pretrained("Rehab-Hamdy/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b34110bf64772ce2534eb5ece4f655efa756720cdb22011c8b07db599ebd4c2
- Size of remote file:
- 5.3 kB
- SHA256:
- 296fe57f87a666e437a908a158a3f1b46f0af46ff699a077aa55c49edc6d6dfb
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