Instructions to use DungHugging/SentimentClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DungHugging/SentimentClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DungHugging/SentimentClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DungHugging/SentimentClassification") model = AutoModelForSequenceClassification.from_pretrained("DungHugging/SentimentClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4948e401349c9524e571f9f8acec4395b3595ff987882ff38e0ad2091f398ecf
- Size of remote file:
- 540 MB
- SHA256:
- 5d2d0e840712ea4f2fe8c726890283776c15a076e5f6a79434694d1a149fa16b
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