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Model: viettelsecurity-ai/cyber-llm-14b Source: Original Platform
2026-09-07 05:00:19 +08:00
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+---
+language:
+- vi
+- en
+base_model:
+- microsoft/phi-4
+pipeline_tag: text-generation
+tags:
+- cybersecurity
+- text-generation-inference
+- transformers
+license: mit
+---
+
+## Model Overview
+|                         |                                                                               |
+|-------------------------|-------------------------------------------------------------------------------|
+| **Developers**          | Microsoft                                                                          |
+| **Architecture**        | 14B parameters, dense decoder-only Transformer model                           |
+| **Inputs**              | Text, best suited for prompts in the chat format                              |
+| **Context length**      | 16K tokens                                                                     |
+| **Outputs**             | Generated text in response to input                                           |
+| **License**             | MIT                                                                           |
+
+## Training Datasets
+Our training data is an extension of the data used for `cyber-llm-14b` and includes a wide variety of sources from:
+
+1. Publicly available blogs, papers, reference from: https://github.com/PEASEC/cybersecurity_dataset.
+
+2. Newly created synthetic, "textbook-like" data for the purpose of teaching cybersecurity (use GPT-4o).
+
+3. Acquired academic books and Q&A datasets
+
+
+## Usage
+
+### Input Formats
+
+Given the nature of the training data, `cyber-llm-14b` is best suited for prompts using the chat format as follows: 
+
+```bash
+<|begin_of_text|><|start_header_id|>user<|end_header_id|>
+Hello!<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+Hey there! How are you?<|eot_id|><|start_header_id|>user<|end_header_id|>
+I'm great thanks!<|eot_id|>
+```
+
+### With `transformers`
+
+```python
+import transformers
+
+pipeline = transformers.pipeline(
+    "text-generation",
+    model="viettelsecurity-ai/cyber-llm-14b",
+    model_kwargs={"torch_dtype": "auto"},
+    device_map="auto",
+)
+
+messages = [
+    {"role": "system", "content": "You are a SOC-tier3"},
+    {"role": "user", "content": "What is the url phishing?"},
+]
+
+outputs = pipeline(messages, max_new_tokens=2048)
+print(outputs[0]["generated_text"][-1])
+```