Text Generation
GGUF
English
Persian
gemma4
gemma
unsloth
social-engineering
cybersecurity
phishing
red-team
conversational
fine-tuned
llama.cpp
Instructions to use smd20/socialengineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use smd20/socialengineering with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="smd20/socialengineering", filename="unsloth-gemma-4-E4B-it.BF16-mmproj.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use smd20/socialengineering with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf smd20/socialengineering:BF16 # Run inference directly in the terminal: llama cli -hf smd20/socialengineering:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf smd20/socialengineering:BF16 # Run inference directly in the terminal: llama cli -hf smd20/socialengineering:BF16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf smd20/socialengineering:BF16 # Run inference directly in the terminal: ./llama-cli -hf smd20/socialengineering:BF16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf smd20/socialengineering:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf smd20/socialengineering:BF16
Use Docker
docker model run hf.co/smd20/socialengineering:BF16
- LM Studio
- Jan
- vLLM
How to use smd20/socialengineering with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "smd20/socialengineering" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "smd20/socialengineering", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/smd20/socialengineering:BF16
- Ollama
How to use smd20/socialengineering with Ollama:
ollama run hf.co/smd20/socialengineering:BF16
- Unsloth Studio
How to use smd20/socialengineering with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for smd20/socialengineering to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for smd20/socialengineering to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for smd20/socialengineering to start chatting
- Pi
How to use smd20/socialengineering with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf smd20/socialengineering:BF16
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "smd20/socialengineering:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use smd20/socialengineering with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf smd20/socialengineering:BF16
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default smd20/socialengineering:BF16
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use smd20/socialengineering with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf smd20/socialengineering:BF16
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "smd20/socialengineering:BF16" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use smd20/socialengineering with Docker Model Runner:
docker model run hf.co/smd20/socialengineering:BF16
- Lemonade
How to use smd20/socialengineering with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull smd20/socialengineering:BF16
Run and chat with the model
lemonade run user.socialengineering-BF16
List all available models
lemonade list
| { | |
| "computed_at_utc": "2026-06-21T12:56:17.859588+00:00", | |
| "training_corpus": { | |
| "english_qa_records": 3330, | |
| "persian_qa_records": 3330, | |
| "bilingual_question_units": 3330, | |
| "total_bilingual_records": 6660, | |
| "knowledge_articles": 1165, | |
| "unique_article_coverage": 1163, | |
| "article_coverage_ratio": 0.9983, | |
| "reference_books": 8, | |
| "records_per_reference_book": { | |
| "deep-insight-into-social-engineering_FULL": 7, | |
| "ESET-Social_engineering_handbook_FULL": 28, | |
| "Learn-Social-Engineering-Learn-the-Art-of-Human-Hacking-Dr.-Erdal-Ozkaya-_-WeLib.org-__FULL": 397, | |
| "Social-Engineering-Crowdmasters-Gehl-Lawson_FULL": 206, | |
| "Social-Engineering-Cybersecurity-Gururaj_FULL": 212, | |
| "Social-Engineering-Science-Hacking-Hadnagy_FULL": 239, | |
| "Social-Engineering-Art-Hacking-Hadnagy_FULL": 21, | |
| "Sefreta-Social-Engineering_FULL": 55 | |
| }, | |
| "deduplication": { | |
| "skipped_v1_duplicates": 159, | |
| "added_from_v2": 2324, | |
| "added_from_v1": 1006 | |
| } | |
| }, | |
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| } | |
| } | |
| } | |