Instructions to use gbarone77/polibert_sa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gbarone77/polibert_sa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gbarone77/polibert_sa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gbarone77/polibert_sa") model = AutoModelForSequenceClassification.from_pretrained("gbarone77/polibert_sa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da9d2d334c6606772f2e6ab063c336f54cee824755c68a9c41ab2703e5f69054
- Size of remote file:
- 443 MB
- SHA256:
- b8f36a67eff19f120d08b911413f85fe75f928780652cbece9ae4ca8ce5986df
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