Instructions to use Fsoft-AIC/dopamin-java-summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/dopamin-java-summary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/dopamin-java-summary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/dopamin-java-summary") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/dopamin-java-summary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 337d8cbd6a9a6a3536d1474c12d7282eb1769eed6da17dc6889c4c845f5248ee
- Size of remote file:
- 4.54 kB
- SHA256:
- cd46eb063dc1c4cc08150bf5f2585aea86a4609091d78bf668384c2f82b332df
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