Instructions to use mradermacher/TreeVGR-7B-CI-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/TreeVGR-7B-CI-i1-GGUF with Transformers:

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

pipe = pipeline("visual-question-answering", model="mradermacher/TreeVGR-7B-CI-i1-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/TreeVGR-7B-CI-i1-GGUF", dtype="auto")

llama-cpp-python

How to use mradermacher/TreeVGR-7B-CI-i1-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mradermacher/TreeVGR-7B-CI-i1-GGUF",
	filename="TreeVGR-7B-CI.i1-IQ1_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 mradermacher/TreeVGR-7B-CI-i1-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf mradermacher/TreeVGR-7B-CI-i1-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 mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/TreeVGR-7B-CI-i1-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 mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/TreeVGR-7B-CI-i1-GGUF with Ollama:
```
ollama run hf.co/mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M
```

Unsloth Studio

How to use mradermacher/TreeVGR-7B-CI-i1-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 mradermacher/TreeVGR-7B-CI-i1-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 mradermacher/TreeVGR-7B-CI-i1-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mradermacher/TreeVGR-7B-CI-i1-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use mradermacher/TreeVGR-7B-CI-i1-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/TreeVGR-7B-CI-i1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/TreeVGR-7B-CI-i1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.TreeVGR-7B-CI-i1-GGUF-Q4_K_M

List all available models

lemonade list

mradermacher commited on Jul 13, 2025

Commit

c25ef33

verified ·

1 Parent(s): dd13300

auto-patch README.md

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README.md +9 -0

README.md CHANGED Viewed

@@ -1,5 +1,9 @@
 ---
 base_model: HaochenWang/TreeVGR-7B-CI
 language:
 - en
 library_name: transformers
@@ -7,6 +11,11 @@ license: apache-2.0
 mradermacher:
   readme_rev: 1
 quantized_by: mradermacher
 ---
 ## About

 ---
 base_model: HaochenWang/TreeVGR-7B-CI
+datasets:
+- HaochenWang/TreeBench
+- HaochenWang/TreeVGR-RL-37K
+- HaochenWang/TreeVGR-SFT-35K
 language:
 - en
 library_name: transformers
 mradermacher:
   readme_rev: 1
 quantized_by: mradermacher
+tags:
+- visual-question-answering
+- visual-grounding
+- visual-reasoning
+- qwen
 ---
 ## About