Instructions to use pablocosta/bertabaporu-large-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pablocosta/bertabaporu-large-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pablocosta/bertabaporu-large-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pablocosta/bertabaporu-large-uncased") model = AutoModelForMaskedLM.from_pretrained("pablocosta/bertabaporu-large-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4dc9cdfdf50972f28d975aab136f228f3a7dc552e3048943b17ace0f7df1414
- Size of remote file:
- 1.48 GB
- SHA256:
- 3314d69cdc7896d347529c5d700755589530b5c2eaacce4393de87431ec67e5f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.