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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e051d966fea0786d8d51faf5378ac3808931885a9b29b6893f948fe3d023cd6
- Size of remote file:
- 14.5 kB
- SHA256:
- 7fd84a35a31decc805621bee8194175d15b652c57174b1244ec7b5b624dc18fe
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