Instructions to use turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF", device_map="auto")

sentence-transformers

How to use turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF with sentence-transformers:

from sentence_transformers import CrossEncoder

model = CrossEncoder("turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF")

query = "Which planet is known as the Red Planet?"
passages = [
	"Venus is often called Earth's twin because of its similar size and proximity.",
	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
]

scores = model.predict([(query, passage) for passage in passages])
print(scores)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF: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 turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF: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 turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull turingevo/Qwen3-VL-Reranker-2B-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3-VL-Reranker-2B-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

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