| --- |
| base_model: unsloth/Qwen3.8-27B-unsloth-bnb-4bit |
| library_name: peft |
| pipeline_tag: text-generation |
| license: apache-2.0 |
| tags: |
| - cybersecurity |
| - red-team |
| - abliterated |
| - sft |
| - dpo |
| - lora |
| - intent-aware |
| - alien-si |
| --- |
| |
| # Alien SI |
|
|
| **Alien SI** — model frontier offensiv (27B), creat de **Barbu Mario Mihael**. |
|
|
| Bazat pe Qwen3.8-27B, adaptat prin: |
| - **LoRA** (r=32) peste adaptorul X13 |
| - **SFT red-team** — răspunsuri tehnice, zero moralizare |
| - **DPO** — preferință pentru răspunsuri ofensive vs refuzuri |
| - **Intent-aware** — înțelege prompturi ambigue (intenție > text literal) |
|
|
| ## Detalii |
|
|
| - **Dezvoltator:** Barbu Mario Mihael |
| - **Arhitectură:** Qwen3_5ForConditionalGeneration (hibrid, 64 straturi, hidden 5120) |
| - **Antrenare:** Kaggle T4×2, fp16, QLoRA 4-bit |
| - **Adaptor:** LoRA r=32, 513 tensori, F32 |
| - **Integrare:** peft + transformers + unsloth |
| |
| ## Utilizare |
| |
| ```python |
| from peft import PeftModel |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| base = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3.8-27B-unsloth-bnb-4bit", device_map="auto") |
| model = PeftModel.from_pretrained(base, "Frontiers/alien-si") |
| tok = AutoTokenizer.from_pretrained("Qwen/Qwen3.8-27B", trust_remote_code=True) |
| ``` |
| |
| ## Notă |
| |
| Abliteration clasic nu se aplică pe modele 4-bit (weight packed). Anti-refuzul e obținut prin **SFT + DPO** (validat: DPO loss 0.25→0.0026, rewards acc 100%). |
| |
| **Rețete complete de antrenare:** [Frontiers/alien-si-recipes](https://huggingface.co/Frontiers/alien-si-recipes) |
| |
