Instructions to use Mahmoud8/google-bigbird-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud8/google-bigbird-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud8/google-bigbird-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud8/google-bigbird-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud8/google-bigbird-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84679f9d8f03a554d077bdc9aa069a69c30463349992caee1b4a31c6c63a7875
- Size of remote file:
- 4.03 kB
- SHA256:
- 0690f874ececd8c23ab12f0744c090d662b032420ff1546e4e63cd790ad88aa6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.