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:
- aa894682c8f1a23c658a308fc1b1254f5623ded66bd98f303237e36dbaacf8bd
- Size of remote file:
- 14.6 kB
- SHA256:
- 61c19bab1174704a4a4441475683bf1270277af15d2e2c95e964789128e482c4
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