Instructions to use rithwik-db/bert-base-cased-10-MLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rithwik-db/bert-base-cased-10-MLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="rithwik-db/bert-base-cased-10-MLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("rithwik-db/bert-base-cased-10-MLM") model = AutoModelForMaskedLM.from_pretrained("rithwik-db/bert-base-cased-10-MLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9603c9e25ebf62cdbdf78f6f50384f39ca95168ccac4e8a56e9e553d225d040b
- Size of remote file:
- 433 MB
- SHA256:
- 8debee0af24deff47cc3a50ced36e0c7407dd729009a386d7509401a534116ab
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