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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. |