Instructions to use KBayoud/bert-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBayoud/bert-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KBayoud/bert-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KBayoud/bert-mlm") model = AutoModelForMaskedLM.from_pretrained("KBayoud/bert-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee2d593b39f73f30fd330f36973fc105fafe6d6f8a18fe7f53c33ebc706362bf
- Size of remote file:
- 5.2 kB
- SHA256:
- 9ef956a8fffdf62513742cd87328c822f6424b431cc70ffe53a60d6d6ec63410
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