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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("microsoft/graphcodebert-base") model = AutoModelForMaskedLM.from_pretrained("microsoft/graphcodebert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Update config.json
Browse filesremove "_name_or_path": "saved_models/graphcodebert_balance/checkpoint-last/pytorch_model.bin",
- config.json +0 -1
config.json
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{
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"_name_or_path": "saved_models/graphcodebert_balance/checkpoint-last/pytorch_model.bin",
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"architectures": [
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"RobertaForMaskedLM"
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],
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{
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"architectures": [
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"RobertaForMaskedLM"
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],
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