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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 317eac1a46ab59531af677ef11f8a6dcfed0bec1c7067bdd4f3fafc99e63b684
- Size of remote file:
- 4.03 kB
- SHA256:
- ed5ba7b0d650147879a2ccbe20ae0e04dccfd7c2c5cf50dfcf51f27f20cc36ab
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