Instructions to use iselabvn/Kali-Terminus-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use iselabvn/Kali-Terminus-v2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="iselabvn/Kali-Terminus-v2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("iselabvn/Kali-Terminus-v2")
model = AutoModelForCausalLM.from_pretrained("iselabvn/Kali-Terminus-v2", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use iselabvn/Kali-Terminus-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "iselabvn/Kali-Terminus-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "iselabvn/Kali-Terminus-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/iselabvn/Kali-Terminus-v2

SGLang

How to use iselabvn/Kali-Terminus-v2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "iselabvn/Kali-Terminus-v2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "iselabvn/Kali-Terminus-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "iselabvn/Kali-Terminus-v2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "iselabvn/Kali-Terminus-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use iselabvn/Kali-Terminus-v2 with Docker Model Runner:
```
docker model run hf.co/iselabvn/Kali-Terminus-v2
```

dungnvt commited on 9 days ago

Commit

416af8d

verified ·

1 Parent(s): afd4fe0

Update README.md

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README.md +39 -38

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@@ -1,41 +1,42 @@
----
-license: apache-2.0
-language:
-- en
-tags:
-- lfm2.5
-- kali-linux
-- terminal-executor
-- tool-calling
-- function-calling
-- executor
-- cybersecurity
-- penetration-testing
-base_model: LiquidAI/LFM2.5-350M-Base
-datasets:
-- iselabvn/Kali-terminal-executor-v2
-library_name: transformers
-pipeline_tag: text-generation
-model-index:
-- name: Kali-Terminus-v2
-  results:
-  - task:
-      type: text-generation
-      name: Shell Command Generation
-    dataset:
-      name: Kali-Terminus Evaluation Suite
-      type: custom
-    metrics:
-    - type: strict_pass_rate
-      value: 92.31
-      name: Strict Pass Rate
-    - type: tool_call_parse_rate
-      value: 100.0
-      name: Tool Call Parse Rate
-    - type: semantic_command_accuracy
-      value: 92.31
-      name: Semantic Command Accuracy
----
 # Kali-Terminus-v2

+---
+license: apache-2.0
+language:
+- en
+tags:
+- lfm2.5
+- kali-linux
+- terminal-executor
+- tool-calling
+- function-calling
+- executor
+- cybersecurity
+- penetration-testing
+base_model: LiquidAI/LFM2.5-350M-Base
+datasets:
+- iselabvn/Kali-terminal-executor-v2
+library_name: transformers
+pipeline_tag: text-generation
+model-index:
+- name: Kali-Terminus-v2
+  results:
+  - task:
+      type: text-generation
+      name: Shell Command Generation
+    dataset:
+      name: Kali-Terminus Evaluation Suite
+      type: custom
+    metrics:
+    - type: strict_pass_rate
+      value: 92.31
+      name: Strict Pass Rate
+    - type: tool_call_parse_rate
+      value: 100
+      name: Tool Call Parse Rate
+    - type: semantic_command_accuracy
+      value: 92.31
+      name: Semantic Command Accuracy
+new_version: iselabvn/Kali-Terminus-v3
+---
 # Kali-Terminus-v2