Instructions to use RayNene/adaption_multi_agent_fraud_bench with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RayNene/adaption_multi_agent_fraud_bench with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/Llama-4-Scout-17B-16E-Instruct_bnb_4bit") model = PeftModel.from_pretrained(base_model, "RayNene/adaption_multi_agent_fraud_bench") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 46521bd37c23372a24b5cf512764d00f6322783db671d59f1f2321c7c3f51165
- Size of remote file:
- 126 kB
- SHA256:
- c25f2dbd86a3068d7f252090707d399f44335237b352a09ef506c9ec908eedcb
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