Instructions to use rithwik-db/bert-base-cased-50-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-50-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-50-MLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("rithwik-db/bert-base-cased-50-MLM") model = AutoModelForMaskedLM.from_pretrained("rithwik-db/bert-base-cased-50-MLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d8f3cab59a58f19cd73c0897906e501c09f911dcd14f15ef0f23e9085e4dd0d
- Size of remote file:
- 433 MB
- SHA256:
- 0cea4aad073bc152b04e0805395df8944513aba61c66b3660dd837e7819491c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.