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rezaduty/gemma4-e2b-docker-container-security

sourceHugging Faceapache-2.0updated 4mo agoView on Hugging Face
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Gemma 4 E2B — Docker & Container Security Expert

A QLoRA fine-tuned version of Gemma 4 E2B Instruct specialized in docker & container security. Specialized in Docker and container security: image hardening, rootless containers, seccomp/AppArmor profiles, runtime threat detection, and container escape techniques and mitigations.

Part of the rezaduty cybersecurity model family.

Expertise

  • —Docker daemon security and socket exposure risks
  • —Image scanning, distroless images, and minimal base images
  • —Rootless containers, user namespaces, and capability dropping
  • —Runtime security with Falco, seccomp, and AppArmor
  • —Container escape techniques and kernel exploit mitigations
  • —Dockerfile best practices and supply-chain integrity

Model Details

PropertyValue
Base modelgoogle/gemma-4-e2b-it (2B parameters)
Fine-tuning methodQLoRA (rank 16, α 16)
DomainDocker & Container Security
LicenseApache 2.0

Usage

python
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
import torch

base_model = "google/gemma-4-e2b-it"
adapter    = "rezaduty/gemma4-e2b-docker-container-security"

tokenizer = AutoTokenizer.from_pretrained(adapter)
model = AutoModelForCausalLM.from_pretrained(
    base_model, torch_dtype=torch.bfloat16, device_map="auto"
)
model = PeftModel.from_pretrained(model, adapter)

messages = [
    {"role": "system", "content": [{"type": "text", "text": "You are an expert in Docker and container security. You provide deep, production-level answers on container hardening, image security, runtime protection, and container escape prevention."}]},
    {"role": "user",   "content": [{"type": "text", "text": "Your question here"}]},
]
inputs = tokenizer.apply_chat_template(
    messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
).to(model.device)
output = model.generate(inputs, max_new_tokens=512, temperature=0.7, top_p=0.9)
print(tokenizer.decode(output[0][inputs.shape[-1]:], skip_special_tokens=True))

System Prompt

You are an expert in Docker and container security. You provide deep, production-level answers on container hardening, image security, runtime protection, and container escape prevention.

See Also