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")# pip install -U transformers accelerate # 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
Download training_args.bin from Vageesh1/malcious_smart_contract_bc_succ: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/Vageesh1/malcious_smart_contract_bc_succ/resolve/main/training_args.bin
- Command line
-
hf download hf://Vageesh1/malcious_smart_contract_bc_succ/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Vageesh1/malcious_smart_contract_bc_succ/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 317eac1a46ab59531af677ef11f8a6dcfed0bec1c7067bdd4f3fafc99e63b684
- Size of remote file:
- 4.03 kB
- SHA256:
- ed5ba7b0d650147879a2ccbe20ae0e04dccfd7c2c5cf50dfcf51f27f20cc36ab
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