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google/functiongemma-270m-it on the iselabvn/Kali-terminal-executor dataset of terminal tool calls using LoRA/QLoRA, and subsequently merging the adapter weights back into the base model to deliver a fast, standalone inference experience without requiring external PEFT dependencies.google/functiongemma-270m-itiselabvn/Kali-terminal-executornmap, gobuster, metasploit, hydra, sqlmap, etc.) with correct flags and parameters based on tool definitions.kali-terminus-v1 runs efficiently on low-resource environments, local VMs, or edge security appliances.[!IMPORTANT] Usage Guidelines & Recommendations:
- Recommended Roles: Designed specifically to act as an Agent Executor within a Multi-Agent System (where a primary planner agent orchestrates goals and delegates execution tasks to this model) or as a specialized Single-Turn Kali Terminal Assistant.
- Not Recommended: Standalone usage as an open-ended general chat assistant or unguided autonomous strategist.
kali-terminus-v1 directly using Hugging Face transformers:1import torch
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4model_id = "kali-terminus-v1" # or local path "./kali-terminus-v1"
5
6# Load tokenizer and model
7tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
8device = "cuda" if torch.cuda.is_available() else "cpu"
9dtype = torch.bfloat16 if torch.cuda.is_available() and torch.cuda.is_bf16_supported() else torch.float32
10
11model = AutoModelForCausalLM.from_pretrained(
12 model_id,
13 torch_dtype=dtype,
14 device_map=device,
15 trust_remote_code=True
16)
17
18# Example prompt
19prompt = "Perform an Nmap stealth scan on target 192.168.1.100 for top 100 ports."
20
21inputs = tokenizer(prompt, return_tensors="pt").to(device)
22with torch.no_grad():
23 outputs = model.generate(**inputs, max_new_tokens=128, do_sample=False)
24
25response = tokenizer.decode(outputs[0], skip_special_tokens=False)
26print(response)iselabvn/Kali-terminal-executorkali-terminus-v1 is designed exclusively for authorized penetration testing, security auditing, educational research, and administrative automation. Users are solely responsible for ensuring compliance with all applicable local, national, and international laws when executing commands generated by this model.