Add specialized README for Cloud IAM & Terraform Security

README.md

@@ -1,22 +1,95 @@
 ---
-base_model: unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+base_model: google/gemma-4-e2b-it
 tags:
 - text-generation-inference
 - transformers
-- unsloth
 - gemma4
-- trl
+- peft
+- lora
+- cybersecurity
+- cloud-security
+- aws
+- iam
+- terraform
+- devsecops
+- cybersecurity
 license: apache-2.0
 language:
 - en
 ---
 
-# Uploaded  model
+# Gemma 4 E2B — Cloud IAM & Terraform Security Expert
 
-- **Developed by:** rezaduty
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+A QLoRA fine-tuned version of [Gemma 4 E2B Instruct](https://huggingface.co/google/gemma-4-e2b-it) specialized in **cloud iam & terraform security**.
+Specialized in **cloud IAM and Terraform security**: least-privilege IAM policy design, ECR image scanning, Terraform state security, and cloud privilege escalation paths.
 
-This gemma4 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
+Part of the [rezaduty cybersecurity model family](https://huggingface.co/rezaduty).
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+---
+
+## Expertise
+
+- AWS IAM least-privilege design and permission boundaries
+- IAM role assumption, OIDC federation, and cross-account access
+- ECR image scanning, lifecycle policies, and pull-through cache security
+- Terraform state file security, remote backends, and drift detection
+- Cloud privilege escalation paths and detection
+- IaC security scanning: Checkov, tfsec, Terrascan
+
+---
+
+## Model Details
+
+| Property | Value |
+|---|---|
+| **Base model** | google/gemma-4-e2b-it (2B parameters) |
+| **Fine-tuning method** | QLoRA (rank 16, α 16) |
+| **Domain** | Cloud IAM & Terraform Security |
+| **License** | Apache 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-cloud-iam-terraform"
+
+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 cloud IAM and infrastructure-as-code security. You provide deep answers on AWS IAM, ECR hardening, Terraform security, and cloud privilege escalation paths."}]},
+    {"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 cloud IAM and infrastructure-as-code security. You provide deep answers on AWS IAM, ECR hardening, Terraform security, and cloud privilege escalation paths.
+```
+
+---
+
+## See Also
+
+- [General cybersecurity model](https://huggingface.co/rezaduty/gemma4-e2b-cybersecurity-interview) — full 646-example dataset
+- [Docker & Container Security](https://huggingface.co/rezaduty/gemma4-e2b-docker-container-security)
+- [Kubernetes Security](https://huggingface.co/rezaduty/gemma4-e2b-kubernetes-security)
+- [AI & LLM Security](https://huggingface.co/rezaduty/gemma4-e2b-ai-llm-security)
+- [All rezaduty models](https://huggingface.co/rezaduty)