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Model: pyToshka/wazuh-llama-3.1-8b-assistant
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- en
+- ru
+- es
+license: llama3.1
+library_name: transformers
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tags:
+- cybersecurity
+- security-analysis
+- wazuh
+- threat-detection
+- llama
+- peft
+- lora
+pipeline_tag: text-generation
+widget:
+- text: 'Analyze this security event: Multiple failed SSH login attempts from 45.142.120.10'
+  example_title: "SSH Brute Force"
+- text: 'Rule Level 12: High importance event detected'
+  example_title: "High Severity Alert"
+model-index:
+- name: wazuh-llama-3.1-8B-assistant
+  results:
+  - task:
+      type: text-generation
+      name: Security Log Analysis
+    metrics:
+    - type: loss
+      value: 0.05
+      name: Training Loss
+    - type: eval_loss
+      value: 0.15
+      name: Validation Loss
+---
+
+# wazuh-llama-3.1-8B-assistant
+
+## Model Details
+
+- **Model Name:** wazuh-llama-3.1-8B-assistant
+- **Base Model:** meta-llama/Llama-3.1-8B-Instruct
+- **License:** llama3.1
+- **Model Type:** Causal Language Model
+- **Architecture:** 8B parameters
+- **Languages:** English, Russian, Spanish (multilingual support)
+- **Training Method:** Supervised Fine-Tuning (SFT) with LoRA adapters
+
+## Model Description
+
+LLaMA 3.1 8B Instruct model fine-tuned for advanced Wazuh security log analysis with instruction-following capabilities.
+
+### Key Features
+
+- Advanced security reasoning and analysis
+- Instruction-following for complex queries
+- Multi-turn conversation support
+- Unsloth optimization on CUDA (2x faster)
+- LoRA fine-tuning for efficiency
+- Comprehensive threat assessment
+
+
+## Wazuh Severity Levels
+
+| Level Range | Severity    | Analysis Approach       |
+|-------------|-------------|-------------------------|
+| 0-5         | Low         | Informational analysis  |
+| 6-10        | Medium      | Detailed investigation  |
+| 11-15       | High/Crit   | Comprehensive response  |
+
+## Usage
+
+### Python API
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("pyToshka/wazuh-llama-3.1-8b-assistant")
+tokenizer = AutoTokenizer.from_pretrained("pyToshka/wazuh-llama-3.1-8b-assistant")
+
+prompt = """Analyze this Wazuh alert and provide:
+1. Threat Level (0-15)
+2. Classification
+3. Risk Assessment
+4. Recommended Actions
+
+Alert: Multiple failed SSH login attempts from 45.142.120.10"""
+
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=512)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+### Expected Output Format
+
+```
+Rule Level: 12 - High importance event
+
+Event Type: SSH brute-force attack detected
+Detailed Reasoning: Multiple failed SSH login attempts indicate brute-force attack...
+Risk Assessment: High - Active credential compromise attempt
+Recommended Actions:
+  1. Block source IP 45.142.120.10 immediately
+  2. Review authentication logs for successful logins
+  3. Enable 2FA if not already active
+Investigation Guidance: Check for related events from same subnet...
+MITRE ATT&CK: T1110.001 - Brute Force: Password Guessing
+```
+
+## Limitations
+
+- Domain: Security/cybersecurity specific
+
+## Citation
+
+```bibtex
+@software{{wazuh_llama_3.1_8B_assistant,
+  title = {{wazuh-llama-3.1-8B-assistant}},
+  author = {{pyToshka}},
+  year = {{2025}},
+  version = {{1.0.0}},
+  url = {{https://huggingface.co/pyToshka/wazuh-llama-3.1-8b-assistant}}
+}}
+```

chat_template.jinja

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+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 Jul 2024" %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message + builtin tools #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if builtin_tools is defined or tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{%- if builtin_tools is defined %}
+    {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- '{"name": "' + tool_call.name + '", ' }}
+            {{- '"parameters": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- "}" }}
+        {%- endif %}
+        {%- if builtin_tools is defined %}
+            {#- This means we're in ipython mode #}
+            {{- "<|eom_id|>" }}
+        {%- else %}
+            {{- "<|eot_id|>" }}
+        {%- endif %}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.56.2"
+}

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