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:
- fa37ace857250c2dc7d78657ae71ec5fbbe3650a6b29b0e99104395c89479abb
- Size of remote file:
- 438 MB
- SHA256:
- 54b3e36653e99acee527d322f3ade338e48d2c31e1d39b79c369768008e06652
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