Instructions to use Fsoft-AIC/dopamin-java-rational with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/dopamin-java-rational with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/dopamin-java-rational")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/dopamin-java-rational") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/dopamin-java-rational") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af0634ba3415b01f9041b133e7420b55da59f578765b17965f737dc0af409b5f
- Size of remote file:
- 612 MB
- SHA256:
- 92521b0b56bd500cad8d44818475e0346fb150c2752c038873c962fea65680b0
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