Instructions to use BugTraceAI/BugTraceAI-CORE-Fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use BugTraceAI/BugTraceAI-CORE-Fast 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 BugTraceAI/BugTraceAI-CORE-Fast
# Run inference directly in the terminal:
llama cli -hf BugTraceAI/BugTraceAI-CORE-Fast

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf BugTraceAI/BugTraceAI-CORE-Fast
# Run inference directly in the terminal:
llama cli -hf BugTraceAI/BugTraceAI-CORE-Fast

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf BugTraceAI/BugTraceAI-CORE-Fast
# Run inference directly in the terminal:
./build/bin/llama cli -hf BugTraceAI/BugTraceAI-CORE-Fast

Use Docker

docker model run hf.co/BugTraceAI/BugTraceAI-CORE-Fast

Llama new
LM Studio
Jan
Ollama
How to use BugTraceAI/BugTraceAI-CORE-Fast with Ollama:
```
ollama run hf.co/BugTraceAI/BugTraceAI-CORE-Fast
```
Unsloth Desktop

How to use BugTraceAI/BugTraceAI-CORE-Fast with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BugTraceAI/BugTraceAI-CORE-Fast

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "BugTraceAI/BugTraceAI-CORE-Fast"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use BugTraceAI/BugTraceAI-CORE-Fast with Docker Model Runner:
```
docker model run hf.co/BugTraceAI/BugTraceAI-CORE-Fast
```

Lemonade

How to use BugTraceAI/BugTraceAI-CORE-Fast with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull BugTraceAI/BugTraceAI-CORE-Fast

Run and chat with the model

lemonade run user.BugTraceAI-CORE-Fast-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use BugTraceAI/BugTraceAI-CORE-Fast with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BugTraceAI/BugTraceAI-CORE-Fast

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 BugTraceAI/BugTraceAI-CORE-Fast

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use BugTraceAI/BugTraceAI-CORE-Fast with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BugTraceAI/BugTraceAI-CORE-Fast

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 "BugTraceAI/BugTraceAI-CORE-Fast" \
  --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"

Albert-yz9yt commited on Mar 13

Commit

a8a5dcb

verified ·

1 Parent(s): bdc1a95

Update documentation with professional security focus and training details

Browse files

Files changed (1) hide show

README.md +16 -8

README.md CHANGED Viewed

@@ -1,20 +1,28 @@
 ---
 license: apache-2.0
 base_model: unsloth/Qwen2.5-Coder-7B-Instruct
 tags:
-- bug-bounty - security - pentesting - fast-inference
 ---
-# BugTraceAI-CORE-Fast
-🚀 Fast & Agile Security Engine (7B Qwen 2.5 Coder Base)
-**Focus:** Speed and precision. Ideal for automated scanning, short payload generation, and quick commands.
-**Output Note:** Optimized for short, concise outputs. Not recommended for long reports.
-## 🛠️ Integration
-Use with the official `BugTraceAI-CORE` orchestrator for automated cybersecurity workflows.
 ---
-_Part of the BugTraceAI Ecosystem._

 ---
 license: apache-2.0
 base_model: unsloth/Qwen2.5-Coder-7B-Instruct
+language:
+  - en
+  - es
 tags:
+- bug-bounty - fast-inference - security - pentesting
 ---
+# ⚡ BugTraceAI-CORE-Fast (7B)
+**The Rapid Response Engine for Automated Pentesting**
+`BugTraceAI-CORE-Fast` es el motor de respuesta rápida del ecosistema. Basado en Qwen 2.5 Coder, ha sido optimizado para ser el primer punto de contacto en escaneos masivos.
+### 🧠 Especialización
+- **Payload Generation:** Generación instantánea de vectores de ataque SQLi, XSS y SSRF.
+- **WAF Testing:** Mutación rápida de payloads para pruebas de evasión unitarias.
+- **CLI Assistant:** Optimizado para entender y generar comandos de `BugTraceAI-CLI`.
+### ⚠️ Limitación de Output
+Este modelo está configurado para respuestas **cortas y concisas**. Es ideal para herramientas automatizadas que requieren un JSON o un comando específico en milisegundos. Para reportes extensos o análisis profundos, utiliza la versión **Pro**.
+## 🛠️ Despliegue e Integración
+Diseñado para trabajar con el orquestador oficial de `BugTraceAI-CORE`.
 ---
+_Creado por BugTraceAI. Construyendo un entorno de seguridad más robusto, reporte a reporte._