Instructions to use tanoManzo/distilbert-attitude with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanoManzo/distilbert-attitude with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tanoManzo/distilbert-attitude")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tanoManzo/distilbert-attitude") model = AutoModelForSequenceClassification.from_pretrained("tanoManzo/distilbert-attitude") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13f30e1c1a8a331c791d3496fc81ed340bc62101ff07a4666ca5a9bbdd97c15e
- Size of remote file:
- 3.52 kB
- SHA256:
- 3e2d35c46e62e82bbd3e1bb99b567b168bbbbee7a1b625c163cf0ed88c4815f9
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