Instructions to use Vageesh1/malcious_smart_contract_bc_succ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vageesh1/malcious_smart_contract_bc_succ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vageesh1/malcious_smart_contract_bc_succ")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Vageesh1/malcious_smart_contract_bc_succ") model = AutoModelForSequenceClassification.from_pretrained("Vageesh1/malcious_smart_contract_bc_succ") - Notebooks
- Google Colab
- Kaggle
Request: need clarification
#2
by bbrhash - opened
Hey
Your model has piqued my interest.
I am trying to develop a smart contract auditing tool trained on datasets. the dataset you used is the most commonly used for analysis.
I wanted to know what is the use of your fine-tuned model. What does it achieve?
Let me know how can we connect further.
Hi thanks for taking intrest in it, I was trying to make a smart contract vulnerability detection, I was using some open dataset, but due to highly unbalanced dataset I was unable to do it so I made some other dataset. If you are looking to connect to me at LinkedIn -https://www.linkedin.com/in/vageesh-jangra-2555a621a
I can share more details if you want.