Instructions to use Ensheng/graphcodebert-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ensheng/graphcodebert-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Ensheng/graphcodebert-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Ensheng/graphcodebert-v1") model = AutoModelForMaskedLM.from_pretrained("Ensheng/graphcodebert-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1992d337595d56607702f1a1305220587e34ccfbe55f75983e40ade28e1656cd
- Size of remote file:
- 499 MB
- SHA256:
- 995d45c4bd43ff596ed3c78377f357adf49ab2692a977ecaeb89919f058792e1
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