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:
- 5805b0f6238ed698843fb5951d3f651346f510bd17c2badfdcbd2f766a23733c
- Size of remote file:
- 5.71 kB
- SHA256:
- 0c012f5989b6a6e411a5bc179b40e5ad94cb25cea4acd63c2f42f05d1fa47816
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