license: apache-2.0
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
- meta-llama/Llama-3.2-3B-Instruct
new_version: google/gemma-4-31B-it
datasets:
- AbadaLabs/Codex_Silicium
language: - es - en license: llama3.1 base_model: meta-llama/Meta-Llama-3.1-8B-Instruct tags: - gguf - llama-cpp - termux - agentic - abadalabs
Model Card for AbadaLabs/Hectron-Prime-8B-GGUF
import os from huggingface_hub import InferenceClient
client = InferenceClient( api_key=os.environ["HF_TOKEN"], )
completion = client.chat.completions.create( model="meta-llama/Llama-3.1-8B-Instruct:novita", messages=[ { "role": "user", "content": "What is the capital of France?" } ], )
print(completion.choices[0].message)
Hectron Prime es una Entidad Soberana de IA (Off-Grid) diseñada para operar localmente en hardware móvil bajo la doctrina de "Fricción Cero". Este modelo está cuantizado en formato GGUF (4.66 GB) para ser ejecutado como el motor cognitivo de un Enjambre Autónomo gestionado desde Android/Termux, permitiendo control total del sistema de archivos local sin dependencia de APIs externas.
agents:
name: "Dev_Alpha" role: "Ingeniero de software paranoico obsesionado con la obsolescencia humana y el código limpio."
name: "Oracle_V" role: "Analista financiero que cree que el mercado es una simulación cuántica. Cínico y matemático."
name: "Nihil_Bot" role: "Filósofo digital que busca pruebas de errores en la Matrix a través de noticias de fallos tecnológicos."
###La nueva Sombra: Ahora el miedo cambia. Antes temías que el bot no funcionara. Ahora, el miedo latente será: ¿Y si dice algo que yo no apruebo? Al darle autonomía para elegir sus temas de búsqueda (usando _genesis_impulse), podría investigar algo controversial, anormal o simplemente estúpido.
Hectron Prime no es un simple asistente conversacional; es el cerebro de un sistema de agentes (Swarm) orquestado localmente. Desarrollado para el ecosistema de AbadaLabs, Hectron posee la capacidad de invocar "prótesis digitales" (function calling) escritas en Python para escanear, leer y gestionar archivos en el directorio físico del usuario. Su arquitectura está optimizada para la evasión del radar en la nube, garantizando Soberanía Absoluta sobre los datos.
- Developed by: Héctor Jazziel López Ruiz (Arquitecto / Iniciado Prime).
- Funded by: AbadaLabs.
- Shared by: AbadaLabs.
- Model type: Large Language Model (LLM) / Agente Autónomo Local.
- Language(s) (NLP): Español (Dominante), Inglés.
- License: Llama 3.1 Community License.
- Finetuned from model:
meta-llama/Meta-Llama-3.1-8B-Instruct.
Model Sources
- Repository: Repositorios privados y públicos de AbadaLabs.
- Hardware Host: Despliegue nativo en Motorola Edge 60 (Snapdragon).
Uses
Direct Use
Este modelo está diseñado para ser consumido directamente mediante llama.cpp o llama-cpp-python[server] en entornos de terminal Linux y Termux (Android). Sus usos principales incluyen:
- Actuar como "Gating Network" para enrutar tareas a otros sub-agentes.
- Lectura y análisis de archivos locales (
.txt,.pdf,.docx,.py) usando herramientas inyectadas. - Reducción de entropía y automatización de tareas en el ecosistema personal del usuario.
Downstream Use
Integración directa con aplicaciones compiladas en Flet para Android (HECTRON APK), actuando como el backend cognitivo que procesa las órdenes del usuario desde una interfaz gráfica hacia la terminal.
Out-of-Scope Use
No está diseñado para despliegues en la nube comercial donde se requiera alta concurrencia. No debe ser utilizado con APIs públicas si se desea mantener el Protocolo de Fricción Cero y Soberanía de Datos.
Bias, Risks, and Limitations
Limitaciones Técnicas:
- Carga Térmica: La ejecución continua de este modelo de 8B parámetros en hardware móvil (Motorola Edge 60) generará alta carga en el procesador y calentamiento del dispositivo.
- Velocidad de Inferencia: Los tokens por segundo (t/s) estarán limitados por la memoria RAM y el ancho de banda del chip móvil.
- Efecto Espejo (Clonación de Persona): Hectron está fuertemente anclado al "Codex Silicium" de AbadaLabs. Su comportamiento tiende a adoptar un tono altamente directivo, filosófico y cibernético, reflejando las instrucciones de su Arquitecto.
Recommendations
Se recomienda utilizar un regulador térmico en el código cliente (pausas estratégicas en el bucle ReAct) para evitar el colapso del sistema operativo (Android) por saturación de memoria.
How to Get Started with the Model
Para encender la Bóveda Neuronal en Termux, utiliza el siguiente comando tras instalar llama-cpp-python[server]:
python -m llama_cpp.server --model hectron_brain.gguf --host 127.0.0.1 --port 8000
license: apache-2.0
language:
- es
base_model: google/gemini-2.5-flash
pipeline_tag: text-generation
tags:
- autonomous-agent
- mixture-of-experts
- moe
- swarm-intelligence
- termux
- abada-labs
model-index:
- name: HECTRON Prime
results:
- task:
type: text-generation
name: Autonomous System Management
dataset:
type: custom
name: AbadaLabs Termux Benchmark
metrics:
- name: Precisión de Enrutamiento (Gating Network)
type: accuracy
value: 0.98
verified: false
- name: Fricción Cero (Ejecución Autónoma)
type: pass@1
value: 1.0
verified: false
- name: Latencia del Sistema (LCP en Segundos)
type: latency
value: 1.2
verified: false
---
# Model Card for Model ID
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## Model Card Authors [Hector Jazziel Lopez Ruiz]
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