Instructions to use Amdalotaibi/fully_supervised_sentiment_model-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amdalotaibi/fully_supervised_sentiment_model-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Amdalotaibi/fully_supervised_sentiment_model-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Amdalotaibi/fully_supervised_sentiment_model-2") model = AutoModelForSequenceClassification.from_pretrained("Amdalotaibi/fully_supervised_sentiment_model-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f95dffddc8127ea5b748437e5cfbe8c6ebcd191df8e203540503a6ba49850d73
- Size of remote file:
- 436 MB
- SHA256:
- 8c25f41952f972a00f1e5173122e2654989494b8d0bcbae47707a86a1d56f176
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