Instructions to use anjandash/JavaBERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anjandash/JavaBERT-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anjandash/JavaBERT-small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anjandash/JavaBERT-small") model = AutoModelForSequenceClassification.from_pretrained("anjandash/JavaBERT-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1dc890655253d5e0fc00ac7f2cf765a96e1f055981c198f7e2e18c7e1463ecf2
- Size of remote file:
- 882 MB
- SHA256:
- c6934f86d1df4265b1c9c7d752e1d0dfc5da506aec6194097a3a71f16c7b0972
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