Instructions to use Itcast/bert-base-cnc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Itcast/bert-base-cnc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Itcast/bert-base-cnc")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Itcast/bert-base-cnc") model = AutoModelForMaskedLM.from_pretrained("Itcast/bert-base-cnc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea2d2b8db7cd624741c1d24f1d1eaf217fab344ed6744d70e9003ea0411d72bf
- Size of remote file:
- 409 MB
- SHA256:
- c1599829ec21a1bb9cfdd79c3696c0dce771c8b14e22d06dcb4942ef7904d765
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.