Instructions to use microsoft/graphcodebert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/graphcodebert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/graphcodebert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("microsoft/graphcodebert-base") model = AutoModelForMaskedLM.from_pretrained("microsoft/graphcodebert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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created a base model card with minimal information
afb641c
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Update config.json
remove "_name_or_path": "saved_models/graphcodebert_balance/checkpoint-last/pytorch_model.bin",2ff2480
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upload flax model
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allow flax
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upload graphcodebert-base model and tokenizer
lushuai8078933 -
initial commit
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