Instructions to use aab20abdullah/qwen_OSINT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aab20abdullah/qwen_OSINT with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="aab20abdullah/qwen_OSINT",
	filename="qwen3-4b-thinking-2507.Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use aab20abdullah/qwen_OSINT with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf aab20abdullah/qwen_OSINT:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf aab20abdullah/qwen_OSINT:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf aab20abdullah/qwen_OSINT:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf aab20abdullah/qwen_OSINT:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf aab20abdullah/qwen_OSINT:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf aab20abdullah/qwen_OSINT:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf aab20abdullah/qwen_OSINT:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf aab20abdullah/qwen_OSINT:Q4_K_M

Use Docker

docker model run hf.co/aab20abdullah/qwen_OSINT:Q4_K_M

LM Studio
Jan

vLLM

How to use aab20abdullah/qwen_OSINT with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aab20abdullah/qwen_OSINT"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aab20abdullah/qwen_OSINT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aab20abdullah/qwen_OSINT:Q4_K_M

Ollama
How to use aab20abdullah/qwen_OSINT with Ollama:
```
ollama run hf.co/aab20abdullah/qwen_OSINT:Q4_K_M
```

Unsloth Studio new

How to use aab20abdullah/qwen_OSINT with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for aab20abdullah/qwen_OSINT to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for aab20abdullah/qwen_OSINT to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for aab20abdullah/qwen_OSINT to start chatting

Pi new

How to use aab20abdullah/qwen_OSINT with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf aab20abdullah/qwen_OSINT:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "aab20abdullah/qwen_OSINT:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use aab20abdullah/qwen_OSINT with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf aab20abdullah/qwen_OSINT:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default aab20abdullah/qwen_OSINT:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use aab20abdullah/qwen_OSINT with Docker Model Runner:
```
docker model run hf.co/aab20abdullah/qwen_OSINT:Q4_K_M
```

Lemonade

How to use aab20abdullah/qwen_OSINT with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull aab20abdullah/qwen_OSINT:Q4_K_M

Run and chat with the model

lemonade run user.qwen_OSINT-Q4_K_M

List all available models

lemonade list

aab20abdullah commited on Apr 9

Commit

ea48328

verified ·

1 Parent(s): 5885a54

Trained with Unsloth - Ollama Modelfile

Browse files

Files changed (1) hide show

Modelfile +54 -0

Modelfile ADDED Viewed

	@@ -0,0 +1,54 @@

+FROM qwen3-4b-thinking-2507.Q5_K_M.gguf
+TEMPLATE """
+{{- $lastUserIdx := -1 -}}
+{{- range $idx, $msg := .Messages -}}
+{{- if eq $msg.Role "user" }}{{ $lastUserIdx = $idx }}{{ end -}}
+{{- end }}
+{{- if or .System .Tools }}<|im_start|>system
+{{ if .System }}
+{{ .System }}
+{{- end }}
+{{- if .Tools }}
+# Tools
+You may call one or more functions to assist with the user query.
+You are provided with function signatures within <tools></tools> XML tags:
+<tools>
+{{- range .Tools }}
+{"type": "function", "function": {{ .Function }}}
+{{- end }}
+</tools>
+For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
+<tool_call>
+{"name": <function-name>, "arguments": <args-json-object>}
+</tool_call>
+{{- end -}}
+<|im_end|>
+{{ end }}
+{{- range $i, $_ := .Messages }}
+{{- $last := eq (len (slice $.Messages $i)) 1 -}}
+{{- if eq .Role "user" }}<|im_start|>user
+{{ .Content }}<|im_end|>
+{{ else if eq .Role "assistant" }}<|im_start|>assistant
+{{ if (and $.IsThinkSet (and .Thinking (or $last (gt $i $lastUserIdx)))) -}}
+<think>{{ .Thinking }}</think>
+{{ end -}}
+{{ if .Content }}{{ .Content }}
+{{- else if .ToolCalls }}<tool_call>
+{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
+{{ end }}</tool_call>
+{{- end }}{{ if not $last }}<|im_end|>
+{{ end }}
+{{- else if eq .Role "tool" }}<|im_start|>user
+<tool_response>
+{{ .Content }}
+</tool_response><|im_end|>
+{{ end }}
+{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant
+{{ end }}
+{{- end }}
+"""