Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use angusleung100/GraphCodeBERT-Base-Solidity-Vulnerability with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use angusleung100/GraphCodeBERT-Base-Solidity-Vulnerability with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="angusleung100/GraphCodeBERT-Base-Solidity-Vulnerability")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("angusleung100/GraphCodeBERT-Base-Solidity-Vulnerability") model = AutoModelForSequenceClassification.from_pretrained("angusleung100/GraphCodeBERT-Base-Solidity-Vulnerability") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31e54ea0b7a7aa971c510de35059174fca4e5f66b3e1f92d9834384ed720434b
- Size of remote file:
- 5.24 kB
- SHA256:
- 7568b661d78c9ce922fd4dd8e386a61478d818bd70f826122493521e700fad73
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.