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:
- b4ec3fb5f4171e9db73abc97131917b2c2805b14b1e319583d9c8b51a9a442fe
- Size of remote file:
- 1.11 GB
- SHA256:
- 272dd158e02f2840d678b37002727f287fbc8d2aa08b22a869d6548e805c7c4f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.