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prithivMLmods
/
Polaris-VGA-4B-Post1.0e

Image-Text-to-Text
Transformers
Safetensors
GGUF
English
qwen3_5
text-generation-inference
object-detection
localization
grounding
visual-grounding-anything
vllm
opencv-python
vlm
llama.cpp
conversational
Model card Files Files and versions
xet
Community
2

Instructions to use prithivMLmods/Polaris-VGA-4B-Post1.0e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="prithivMLmods/Polaris-VGA-4B-Post1.0e")
    messages = [
        {
            "role": "user",
            "content": [
                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
                {"type": "text", "text": "What animal is on the candy?"}
            ]
        },
    ]
    pipe(text=messages)
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("prithivMLmods/Polaris-VGA-4B-Post1.0e")
    model = AutoModelForImageTextToText.from_pretrained("prithivMLmods/Polaris-VGA-4B-Post1.0e")
    messages = [
        {
            "role": "user",
            "content": [
                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
                {"type": "text", "text": "What animal is on the candy?"}
            ]
        },
    ]
    inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
  • llama-cpp-python

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="prithivMLmods/Polaris-VGA-4B-Post1.0e",
    	filename="GGUF/Polaris-VGA-4B-Post1.0e.BF16.gguf",
    )
    
    llm.create_chat_completion(
    	messages = [
    		{
    			"role": "user",
    			"content": [
    				{
    					"type": "text",
    					"text": "Describe this image in one sentence."
    				},
    				{
    					"type": "image_url",
    					"image_url": {
    						"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    					}
    				}
    			]
    		}
    	]
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • llama.cpp

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    # Run inference directly in the terminal:
    llama-cli -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    # Run inference directly in the terminal:
    llama-cli -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    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 prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    # Run inference directly in the terminal:
    ./llama-cli -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    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 prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    Use Docker
    docker model run hf.co/prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
  • LM Studio
  • Jan
  • vLLM

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "prithivMLmods/Polaris-VGA-4B-Post1.0e"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "prithivMLmods/Polaris-VGA-4B-Post1.0e",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
  • SGLang

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e 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 "prithivMLmods/Polaris-VGA-4B-Post1.0e" \
        --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": "prithivMLmods/Polaris-VGA-4B-Post1.0e",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
    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 "prithivMLmods/Polaris-VGA-4B-Post1.0e" \
            --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": "prithivMLmods/Polaris-VGA-4B-Post1.0e",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
  • Ollama

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with Ollama:

    ollama run hf.co/prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
  • Unsloth Studio new

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e 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 prithivMLmods/Polaris-VGA-4B-Post1.0e 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 prithivMLmods/Polaris-VGA-4B-Post1.0e to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for prithivMLmods/Polaris-VGA-4B-Post1.0e to start chatting
  • Pi new

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    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": "prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    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 prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    Run Hermes
    hermes
  • Docker Model Runner

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with Docker Model Runner:

    docker model run hf.co/prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
  • Lemonade

    How to use prithivMLmods/Polaris-VGA-4B-Post1.0e with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull prithivMLmods/Polaris-VGA-4B-Post1.0e:BF16
    Run and chat with the model
    lemonade run user.Polaris-VGA-4B-Post1.0e-BF16
    List all available models
    lemonade list
Polaris-VGA-4B-Post1.0e / Visual-Grounding-Anything
46 kB
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  • 1 contributor
History: 1 commit
prithivMLmods's picture
prithivMLmods
upload source [image_detection, image_pointer, video_object_tracking, video_points_tracking] βœ… (#2)
865e978 2 months ago
  • image_detection_app.py
    6.12 kB
    upload source [image_detection, image_pointer, video_object_tracking, video_points_tracking] βœ… (#2) 2 months ago
  • image_pointer_app.py
    7.39 kB
    upload source [image_detection, image_pointer, video_object_tracking, video_points_tracking] βœ… (#2) 2 months ago
  • video_object_tracking_app.py
    14.5 kB
    upload source [image_detection, image_pointer, video_object_tracking, video_points_tracking] βœ… (#2) 2 months ago
  • video_points_tracking_app.py
    18 kB
    upload source [image_detection, image_pointer, video_object_tracking, video_points_tracking] βœ… (#2) 2 months ago