Instructions to use NTUYG/FG-CodeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTUYG/FG-CodeBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NTUYG/FG-CodeBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NTUYG/FG-CodeBERT") model = AutoModelForMaskedLM.from_pretrained("NTUYG/FG-CodeBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84e77b71f9501f736fbe39f3055d3cdb64cb57564abe7e6b7b73f9f5c17713c6
- Size of remote file:
- 499 MB
- SHA256:
- 360f7558d74d72801aa68d3717b5ba6c6c3a7d730bf6cb2c1bc848a5c1df67d9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.