Instructions to use Fsoft-AIC/dopamin-java-usage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/dopamin-java-usage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/dopamin-java-usage")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/dopamin-java-usage") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/dopamin-java-usage") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37a269c1fc2ab9f5c6143f04f4e59a4cf1cbaf493f8eebeefaac77147df7a52d
- Size of remote file:
- 4.54 kB
- SHA256:
- a8190dd2a2fa51cd6998f46f14638160c517c519eef1e9e3bb5b5dcdf7cb1f21
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.