---
pipeline_tag: text-generation
library_name: transformers
---

# ASGTransformer

`ASGTransformer` is a unified, catalog-grounded defensive cybersecurity scenario
model. It bundles the semantic encoder, scenario planner, duration planner,
professional text renderer, and knowledge catalog in one Hugging Face repository.

## Pipeline

`Input Text -> Encoder -> Scenario Planner -> Duration Planner -> Text Generator`

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "wasmdashai/asg-v1"

tokenizer = AutoTokenizer.from_pretrained(
    model_id,
    trust_remote_code=True,
)

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    trust_remote_code=True,
    torch_dtype="auto",
    device_map="auto",
)

result = model.generate_scenario(
    tokenizer,
    (
        "Create an authorized defensive enterprise scenario focused on "
        "phishing awareness, credential protection, and response readiness."
    ),
    language="en",
    max_new_tokens=384,
    do_sample=True,
    temperature=0.7,
    top_p=0.9,
)

print(result["text"])
print(result["estimated_duration_minutes"])
print(result["scenario_type"])
```

The model is intended for authorized defensive training, tabletop exercises,
detection engineering, control validation, and incident-response preparation.