Instructions to use researchworkai/Sentiment-roBERTa-Twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use researchworkai/Sentiment-roBERTa-Twitter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="researchworkai/Sentiment-roBERTa-Twitter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("researchworkai/Sentiment-roBERTa-Twitter") model = AutoModelForSequenceClassification.from_pretrained("researchworkai/Sentiment-roBERTa-Twitter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec6e456fa192b9b32e45bf8b14329b0702a1ab95eb1db46e83243c8e8198cf82
- Size of remote file:
- 499 MB
- SHA256:
- c37a3484c55954cd75b336a85f1e0c023ae874f3a73b05d2418dd04828e293b1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.