Text Generation
PEFT
Safetensors
English
cybersecurity
soc-triage
threat-detection
qlora
qwen3
conversational
Instructions to use minar-svn/ThreatQwen-1.7B-Detect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minar-svn/ThreatQwen-1.7B-Detect with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-1.7B-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "minar-svn/ThreatQwen-1.7B-Detect") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf2aa5fe70d26b5c71d58c54df059fc5807f7e4c5dbaba5f9ff5c1a07b86afe4
- Size of remote file:
- 1.47 kB
- SHA256:
- 7f662027000969bd5c53794b1cc5f79566a2685a3b174c35097cd8419c58d83d
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