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")# 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
File size: 1,443 Bytes
c61043c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | {
"add_cross_attention": false,
"architectures": [
"RobertaForSequenceClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"classifier_dropout": null,
"dtype": "float32",
"eos_token_id": 2,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "safe",
"1": "reentrancy",
"2": "access_control",
"3": "tx_origin_auth",
"4": "integer_overflow",
"5": "unsafe_delegatecall",
"6": "weak_randomness",
"7": "unbounded_loop",
"8": "redundant_storage",
"9": "gas_optimization",
"10": "best_practice",
"11": "other"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"is_decoder": false,
"label2id": {
"access_control": 2,
"best_practice": 10,
"gas_optimization": 9,
"integer_overflow": 4,
"other": 11,
"redundant_storage": 8,
"reentrancy": 1,
"safe": 0,
"tx_origin_auth": 3,
"unbounded_loop": 7,
"unsafe_delegatecall": 5,
"weak_randomness": 6
},
"layer_norm_eps": 1e-05,
"max_position_embeddings": 514,
"model_type": "roberta",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"output_past": true,
"pad_token_id": 1,
"problem_type": "single_label_classification",
"tie_word_embeddings": true,
"transformers_version": "5.16.1",
"type_vocab_size": 1,
"use_cache": true,
"vocab_size": 50265
}
|