Instructions to use cruiser/roberta-twitter-sentiment-extraction_eval_32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/roberta-twitter-sentiment-extraction_eval_32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/roberta-twitter-sentiment-extraction_eval_32")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/roberta-twitter-sentiment-extraction_eval_32") model = AutoModelForSequenceClassification.from_pretrained("cruiser/roberta-twitter-sentiment-extraction_eval_32") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened almost 3 years ago
by
SFconvertbot