Instructions to use MatthewsO3/GraphCode-CErl-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatthewsO3/GraphCode-CErl-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MatthewsO3/GraphCode-CErl-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MatthewsO3/GraphCode-CErl-base") model = AutoModelForMaskedLM.from_pretrained("MatthewsO3/GraphCode-CErl-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d203e02dbe844abd2ba014f5a738215811f2b995772b860301e5fbc4f76c045
- Size of remote file:
- 499 MB
- SHA256:
- bb7ace68d9bd7fda388055d0e91b91f0380b5b2c98eb859d1d09bebe70879a38
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