Text Classification
Transformers
Safetensors
English
roberta
code
solidity
smart-contracts
vulnerability-detection
graphcodebert
Eval Results (legacy)
Instructions to use tanaymitra01/graphcodebert-vulnerability-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanaymitra01/graphcodebert-vulnerability-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tanaymitra01/graphcodebert-vulnerability-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tanaymitra01/graphcodebert-vulnerability-detector") model = AutoModelForSequenceClassification.from_pretrained("tanaymitra01/graphcodebert-vulnerability-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload SmartBugs-Wild fine-tuned Graph CodeBERT checkpoint
Browse files- config.json +59 -0
- label_map.json +44 -0
- model.safetensors +3 -0
config.json
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{
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"add_cross_attention": false,
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"architectures": [
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"RobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"dtype": "float32",
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "safe",
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"1": "reentrancy",
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"2": "access_control",
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"3": "tx_origin_auth",
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"4": "integer_overflow",
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"5": "unsafe_delegatecall",
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"6": "weak_randomness",
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"7": "unbounded_loop",
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"8": "redundant_storage",
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"9": "gas_optimization",
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"10": "best_practice",
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"11": "other"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"is_decoder": false,
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"label2id": {
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"access_control": 2,
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"best_practice": 10,
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"gas_optimization": 9,
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"integer_overflow": 4,
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"other": 11,
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"redundant_storage": 8,
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"reentrancy": 1,
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"safe": 0,
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"tx_origin_auth": 3,
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"unbounded_loop": 7,
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"unsafe_delegatecall": 5,
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"weak_randomness": 6
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 1,
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"problem_type": "single_label_classification",
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"tie_word_embeddings": true,
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"transformers_version": "5.16.1",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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label_map.json
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{
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"labels": [
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"safe",
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"reentrancy",
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"access_control",
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"tx_origin_auth",
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"integer_overflow",
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"unsafe_delegatecall",
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"weak_randomness",
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"unbounded_loop",
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"redundant_storage",
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"gas_optimization",
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"best_practice",
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"other"
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],
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"id2label": {
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"0": "safe",
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"1": "reentrancy",
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"2": "access_control",
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"3": "tx_origin_auth",
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"4": "integer_overflow",
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"5": "unsafe_delegatecall",
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"6": "weak_randomness",
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"7": "unbounded_loop",
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"8": "redundant_storage",
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"9": "gas_optimization",
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"10": "best_practice",
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"11": "other"
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},
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"label2id": [
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"safe",
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"reentrancy",
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"access_control",
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"tx_origin_auth",
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"integer_overflow",
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"unsafe_delegatecall",
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"weak_randomness",
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"unbounded_loop",
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"redundant_storage",
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"gas_optimization",
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"best_practice",
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"other"
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]
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:abade38beac60146616d8e09142b18d2ff8123909446f217a3e52141ded3d814
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size 498643584
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