Instructions to use Drigoro/roberta_normal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Drigoro/roberta_normal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Drigoro/roberta_normal")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Drigoro/roberta_normal") model = AutoModelForSequenceClassification.from_pretrained("Drigoro/roberta_normal") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72727d9bffabfbff806d3826f48caa7083598546f6a9ca8c78c28cf06a82b518
- Size of remote file:
- 499 MB
- SHA256:
- 2aed4c80c9347f6a094e17ff277b3b4a536b995b9c0c6078b0752ae8ff98cf8f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.