Instructions to use tiya1012/emocounterhate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiya1012/emocounterhate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tiya1012/emocounterhate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tiya1012/emocounterhate") model = AutoModelForSequenceClassification.from_pretrained("tiya1012/emocounterhate") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bba92a7a46b69db4d885174caccd68ea92807139981fbc20273605911f476eb4
- Size of remote file:
- 268 MB
- SHA256:
- 93b7ba2fdfa5ce2d16943248c56b9db3b1ccc1d63ced1573597e77692bc3e88d
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