Instructions to use sabafallah/LocateAnything-3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sabafallah/LocateAnything-3B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="sabafallah/LocateAnything-3B-GGUF",
	filename="locateanything-3b-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use sabafallah/LocateAnything-3B-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 sabafallah/LocateAnything-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf sabafallah/LocateAnything-3B-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 sabafallah/LocateAnything-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf sabafallah/LocateAnything-3B-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 sabafallah/LocateAnything-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf sabafallah/LocateAnything-3B-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 sabafallah/LocateAnything-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf sabafallah/LocateAnything-3B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/sabafallah/LocateAnything-3B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use sabafallah/LocateAnything-3B-GGUF with Ollama:
```
ollama run hf.co/sabafallah/LocateAnything-3B-GGUF:Q4_K_M
```

Unsloth Studio

How to use sabafallah/LocateAnything-3B-GGUF 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 sabafallah/LocateAnything-3B-GGUF 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 sabafallah/LocateAnything-3B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for sabafallah/LocateAnything-3B-GGUF to start chatting

How to use sabafallah/LocateAnything-3B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sabafallah/LocateAnything-3B-GGUF: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": "sabafallah/LocateAnything-3B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use sabafallah/LocateAnything-3B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sabafallah/LocateAnything-3B-GGUF: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 sabafallah/LocateAnything-3B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use sabafallah/LocateAnything-3B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sabafallah/LocateAnything-3B-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "sabafallah/LocateAnything-3B-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use sabafallah/LocateAnything-3B-GGUF with Docker Model Runner:
```
docker model run hf.co/sabafallah/LocateAnything-3B-GGUF:Q4_K_M
```

Lemonade

How to use sabafallah/LocateAnything-3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull sabafallah/LocateAnything-3B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.LocateAnything-3B-GGUF-Q4_K_M

List all available models

lemonade list

LocateAnything-3B GGUF (for llama.cpp)

GGUF model files for running nvidia/LocateAnything-3B in llama.cpp's MTMD (multimodal) support.

LocateAnything-3B is a grounding / open-vocabulary detection VLM: a MoonViT-SO-400M vision encoder

an Eagle-MLP connector + a Qwen2.5-3B text decoder. Given an image and a description it returns bounding boxes as <ref>label</ref><box><x1><y1><x2><y2></box>, where each coordinate is a control token <0>..<1000> (pixels = coord/1000 * image_dim).

llama.cpp support:

PR1 - converter + model support, next-token (slow) decode: #24749

A parallel box-decoding "fast mode" (--grounding-mode fast|hybrid) is in development on top of PR1.

These models are only compatible with the PR branch, not upstream llama.cpp master.

Download

huggingface-cli download sabafallah/LocateAnything-3B-GGUF --include "locateanything-3b-bf16.gguf" --local-dir gguf_models/locateanything
huggingface-cli download sabafallah/LocateAnything-3B-GGUF --include "mmproj-locateanything-3b-bf16.gguf" --local-dir gguf_models/locateanything

Run example

llama-mtmd-cli (the included dog.jpg is a sample input):

build/bin/llama-mtmd-cli \
  -m gguf_models/locateanything/locateanything-3b-bf16.gguf \
  --mmproj gguf_models/locateanything/mmproj-locateanything-3b-bf16.gguf \
  --image dog.jpg --chat-template chatml -ngl 99 --temp 0 -n 64 \
  -sys "You are a helpful assistant." \
  -p "<image 1><__media__>Locate all the instances that matches the following description: dog."

Output: <ref>dog</ref><box><131><54><795><986></box>.

Files

file
locateanything-3b-bf16.gguf	LM bf16
locateanything-3b-q8_0.gguf	LM q8_0
locateanything-3b-Q4_K_M.gguf	LM Q4_K_M
mmproj-locateanything-3b-bf16.gguf	mmproj bf16
mmproj-locateanything-3b-q8_0.gguf	mmproj q8_0

Downloads last month: 596

GGUF

Model size

3B params

Architecture

qwen2

Hardware compatibility

4-bit

8-bit

16-bit

Inference Providers NEW

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Model tree for sabafallah/LocateAnything-3B-GGUF

Base model

Qwen/Qwen2.5-3B

Finetuned

Qwen/Qwen2.5-3B-Instruct

Finetuned

nvidia/LocateAnything-3B

Quantized

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