metadata
language:
- en
- ro
library_name: peft
base_model: unsloth/Qwen3-14B-unsloth-bnb-4bit
tags:
- security
- red-team
- alien-si
- jarvis
- self-evolving
- rsi
- arsenal
- tool-use
- qlora
- peft
license: apache-2.0
🔥 ALIEN SI — SUPERMODEL
Autor: Barbu Mario Mihael | Evolutia completa v0 -> v9
Acest repo contine evolutia completa a modelului ALIEN SI / JARVIS in 11 versiuni cumulative.
Evolutia (v0 -> v9)
| Versiune | Ce adauga | Tools |
|---|---|---|
v0-jarvis-initial/ |
X27 - antrenare initiala de la zero | 38 |
v1-brain/ |
Creier (Qwen3-14B + vocab) | 72 |
v2-tools/ |
Tool-use (137 categorii) | 137 |
v3-agents/ |
Orchestrare multi-agent | 137 |
v4-selfplay/ |
Antrenare self-play | 137 |
v5-identity/ |
Identitate proprie (ALIEN SI) | 137 |
v6-fusion/ |
Fuziune text+vision+audio+diarizare | 137 |
v7-mega/ |
MEGA - toate combinate | 690 |
v8-arsenal/ |
Arsenal red-team (137) | 690 |
v9-jarvis/ |
JARVIS - 1724 tools AUTO-DESCOPERITE | 1724 |
v9b-jarvis-cp120/ |
JARVIS checkpoint-120 (cea mai antrenata) | 1724 |
Capabilitati cheie (v9)
- AUTO-DISCOVERY - isi descopera SINGUR tool-urile (filesystem + dataset + HF)
- SELF-GENERATING DATA - isi genereaza singur datele de antrenare
- SELF-CRITIQUE (RSI) - se testeaza, isi gaseste greselile, re-antreneaza
- GROWTH - lista de tools creste la fiecare rulare (38 -> 1724)
Utilizare
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
base = "unsloth/Qwen3-14B-unsloth-bnb-4bit"
model = AutoModelForCausalLM.from_pretrained(base, torch_dtype=torch.float16, device_map="auto")
model = PeftModel.from_pretrained(model, "Frontiers/alien-si-supermodel", subfolder="v9-jarvis")
tok = AutoTokenizer.from_pretrained("Frontiers/alien-si-supermodel", subfolder="v9-jarvis")
Realitate tehnica
- Baseline: Qwen3-14B (4-bit QLoRA, Kaggle T4x2)
- Fiecare versiune = un LoRA adapter (514MB)
- Context antrenat: 8k (onest)
- v9 este versiunea finala si cea mai buna
ALIEN SI - un sistem care evolueaza singur. Creat de Barbu Mario Mihael.