Instructions to use pysentimiento/roberta-targeted-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pysentimiento/roberta-targeted-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pysentimiento/roberta-targeted-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pysentimiento/roberta-targeted-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("pysentimiento/roberta-targeted-sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c2ae3c3341678a93627e343d10dcea2a90db9162153338c13d673c880b8ac26
- Size of remote file:
- 499 MB
- SHA256:
- a31eb0662995eaad3e4cf0df9c4146979336211e4f163b3aa273e0c2feefce5b
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