Instructions to use VECTORVV1/Qwen3VL-8B-Balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use VECTORVV1/Qwen3VL-8B-Balanced with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="VECTORVV1/Qwen3VL-8B-Balanced",
	filename="Qwen3VL-8B-Uncensored-HauhauCS-Balanced-BF16.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use VECTORVV1/Qwen3VL-8B-Balanced with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf VECTORVV1/Qwen3VL-8B-Balanced: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 VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf VECTORVV1/Qwen3VL-8B-Balanced: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 VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M

Use Docker

docker model run hf.co/VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M

LM Studio
Jan
Ollama
How to use VECTORVV1/Qwen3VL-8B-Balanced with Ollama:
```
ollama run hf.co/VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M
```

Unsloth Studio new

How to use VECTORVV1/Qwen3VL-8B-Balanced 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 VECTORVV1/Qwen3VL-8B-Balanced 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 VECTORVV1/Qwen3VL-8B-Balanced to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for VECTORVV1/Qwen3VL-8B-Balanced to start chatting

Pi new

How to use VECTORVV1/Qwen3VL-8B-Balanced with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf VECTORVV1/Qwen3VL-8B-Balanced: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": "Qwen3VL-8B-Balanced"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use VECTORVV1/Qwen3VL-8B-Balanced with Docker Model Runner:
```
docker model run hf.co/VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M
```

Lemonade

How to use VECTORVV1/Qwen3VL-8B-Balanced with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull VECTORVV1/Qwen3VL-8B-Balanced:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3VL-8B-Balanced-Q4_K_M

List all available models

lemonade list

VECTORVV1

HauhauCS commited on 23 days ago

Commit

604e41f

0 Parent(s):

Duplicate from HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Balanced

Browse files

Co-authored-by: HauHau <HauhauCS@users.noreply.huggingface.co>

Files changed (7) hide show

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README.md ADDED Viewed

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+---
+license: apache-2.0
+tags:
+  - uncensored
+  - qwen3
+  - vision
+  - multimodal
+language:
+  - en
+  - zh
+---
+# Qwen3VL-8B-Uncensored-HauhauCS-Balanced
+> **[Join the Discord](https://discord.gg/SZ5vacTXYf)** for updates, roadmaps, projects, or just to chat.
+Qwen3VL-8B uncensored by HauhauCS.
+## About
+No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.
+These are meant to be the best lossless uncensored models out there.
+## Balanced vs Aggressive
+This is the **Balanced** variant with moderate uncensoring. Best for agentic coding and reliability-critical tasks.
+For stronger uncensoring when this variant refuses too much, use the [Aggressive](https://huggingface.co/HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive) variant instead.
+## Downloads
+| File | Quant | Size |
+|------|-------|------|
+| Qwen3VL-8B-Uncensored-HauhauCS-Balanced-BF16.gguf | BF16 | 16 GB |
+| Qwen3VL-8B-Uncensored-HauhauCS-Balanced-Q8_0.gguf | Q8_0 | 8.2 GB |
+| Qwen3VL-8B-Uncensored-HauhauCS-Balanced-Q6_K.gguf | Q6_K | 6.3 GB |
+| Qwen3VL-8B-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf | Q4_K_M | 4.7 GB |
+| Qwen3VL-8B-Uncensored-HauhauCS-Balanced-mmproj-f16.gguf | mmproj | 1.1 GB |
+## Specs
+- 8B parameters
+- 256K context
+- Vision-language model (requires mmproj file for image input)
+- Based on [Qwen3-VL-8B](https://huggingface.co/Qwen/Qwen3-VL-8B)
+## Usage
+Works with llama.cpp, LM Studio, koboldcpp, etc.
+**For vision capabilities**, load both the main model and the mmproj file.
+llama.cpp example:
+```bash
+./llama-cli -m Qwen3VL-8B-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf \
+  --mmproj Qwen3VL-8B-Uncensored-HauhauCS-Balanced-mmproj-f16.gguf \
+  --image your_image.jpg \
+  -p "Describe this image"
+```