Instructions to use meloneneneis/graphcodebert-base-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use meloneneneis/graphcodebert-base-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="meloneneneis/graphcodebert-base-german")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("meloneneneis/graphcodebert-base-german") model = AutoModelForMaskedLM.from_pretrained("meloneneneis/graphcodebert-base-german") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7486f0efc9329443ede890ab32d651a3102f1670d31580eaa8d37c87d491d16
- Size of remote file:
- 514 MB
- SHA256:
- d8961dc0f85e52dea768c6ef5a63a3f66f9db5f7802c0e24a3bfed8708caae87
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