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:
- 4160c034d1fded16fbec439f6e2025b019792d10a0400b4b699f94f1a50c17ea
- Size of remote file:
- 514 MB
- SHA256:
- 6838a2107ccdcfad2c369360962f8d2f86603e99f6e28ac81eb202e2fac91273
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