Instructions to use 51la5/roberta-base-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 51la5/roberta-base-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="51la5/roberta-base-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("51la5/roberta-base-sentiment") model = AutoModelForSequenceClassification.from_pretrained("51la5/roberta-base-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c52a7b1f81853a6ff902c3c37997b692d12cfb475ff3b3e718805267e52fc398
- Size of remote file:
- 501 MB
- SHA256:
- 6f609c29c3a4b20c2d966a5760fca006ee3a9846b9a69e4f1f9a0ef9b93f4b36
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.