Instructions to use neulab/codebert-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neulab/codebert-python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="neulab/codebert-python")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("neulab/codebert-python") model = AutoModelForMaskedLM.from_pretrained("neulab/codebert-python") - Inference
- Notebooks
- Google Colab
- Kaggle
This is a microsoft/codebert-base-mlm model, trained for 1,000,000 steps (with batch_size=32) on Python code from the codeparrot/github-code-clean dataset, on the masked-language-modeling task.
It is intended to be used in CodeBERTScore: https://github.com/neulab/code-bert-score, but can be used for any other model or task.
For more information, see: https://github.com/neulab/code-bert-score