Text Generation
Joblib
English
mixtral
cybersecurity
threat-intelligence
malware-analysis
forgeagent
awq
quantized
thinking-model
progressive-learning
knowledge-consolidation
4-bit precision
Instructions to use Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- vLLM
How to use Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1
- SGLang
How to use Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1 with Docker Model Runner:
docker model run hf.co/Ro0tuX/MalForge-ThreatOracle-Mixtral-AWQ-v1
MalForge ThreatOracle - ForgeAgent Enhanced Cybersecurity AI
π Model Overview
This is a ForgeAgent-enhanced cybersecurity AI model specifically trained for threat analysis, malware research, and cybersecurity applications. The model has been enhanced through the ForgeAgent knowledge consolidation system with real-world cybersecurity knowledge from the MalForge platform.
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