Instructions to use ahmedabdelali/bert-base-qarib with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedabdelali/bert-base-qarib with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ahmedabdelali/bert-base-qarib")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ahmedabdelali/bert-base-qarib") model = AutoModelForMaskedLM.from_pretrained("ahmedabdelali/bert-base-qarib", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 498056db904cbac211ac40126cd1d9288df858d89b46c79272a15a9ccc05b0f2
- Size of remote file:
- 1.63 GB
- SHA256:
- 363194c0e29873687913ae53b5ad4e324be46eded369e0d507e2516e0aebf43f
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