Instructions to use dzungpham/graphcodebert-code-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzungpham/graphcodebert-code-classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dzungpham/graphcodebert-code-classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update graphcodebert-base-lowLR-highBatchSize/checkpoint-500/trainer_state.json
Browse files
graphcodebert-base-lowLR-highBatchSize/checkpoint-500/trainer_state.json
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@@ -3,7 +3,7 @@
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.4892367906066536,
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"eval_steps":
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"global_step": 500,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.4892367906066536,
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"eval_steps": 50,
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"global_step": 500,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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