Instructions to use ynklab/XCodeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ynklab/XCodeBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ynklab/XCodeBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ynklab/XCodeBERT") model = AutoModelForMaskedLM.from_pretrained("ynklab/XCodeBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d54898f8223d5fe89fbe48c5889338af853d9cd1df4fb3bd64a28202e3763a8
- Size of remote file:
- 1.11 GB
- SHA256:
- c2d3e48fff0ae25588232a0f88ecff8d26e359cc913d583ce218be9a01562aa0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.