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:
- ee9bd84fef9184a34d6a81c2740cf80035ea82490d5595334849482d621dec07
- Size of remote file:
- 3.64 kB
- SHA256:
- 2ffbb88fcd63a48203955b70048adcb73d589bfde654b53ca5e8f23536ed6234
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.