Instructions to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="VECTORVV1/DeepSeek-R1-Distill-Qwen-7B", filename="DeepSeek-R1-Distill-Qwen-7B-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/DeepSeek-R1-Distill-Qwen-7B with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16 # Run inference directly in the terminal: llama-cli -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16 # Run inference directly in the terminal: llama-cli -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B: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 VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16 # Run inference directly in the terminal: ./llama-cli -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B: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 VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16
Use Docker
docker model run hf.co/VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16
- LM Studio
- Jan
- Ollama
How to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B with Ollama:
ollama run hf.co/VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16
- Unsloth Studio new
How to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B 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/DeepSeek-R1-Distill-Qwen-7B 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/DeepSeek-R1-Distill-Qwen-7B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for VECTORVV1/DeepSeek-R1-Distill-Qwen-7B to start chatting
- Pi new
How to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B: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": "VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf VECTORVV1/DeepSeek-R1-Distill-Qwen-7B: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 VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16
Run Hermes
hermes
- Docker Model Runner
How to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B with Docker Model Runner:
docker model run hf.co/VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16
- Lemonade
How to use VECTORVV1/DeepSeek-R1-Distill-Qwen-7B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull VECTORVV1/DeepSeek-R1-Distill-Qwen-7B:BF16
Run and chat with the model
lemonade run user.DeepSeek-R1-Distill-Qwen-7B-BF16
List all available models
lemonade list
| license: apache-2.0 | |
| tags: | |
| - uncensored | |
| - qwen3 | |
| - vision | |
| - multimodal | |
| language: | |
| - en | |
| - zh | |
| # Qwen3VL-8B-Uncensored-HauhauCS-Aggressive | |
| > **[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. | |
| ## Aggressive vs Balanced | |
| This is the **Aggressive** variant with stronger uncensoring. Use this when the Balanced variant refuses too much. | |
| For agentic coding and reliability-critical tasks, use the [Balanced](https://huggingface.co/HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Balanced) variant instead. | |
| ## Downloads | |
| | File | Quant | Size | | |
| |------|-------|------| | |
| | Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-BF16.gguf | BF16 | 16 GB | | |
| | Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q8_0.gguf | Q8_0 | 8.2 GB | | |
| | Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf | Q6_K | 6.3 GB | | |
| | Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q4_K_M.gguf | Q4_K_M | 4.7 GB | | |
| | Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-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-Aggressive-Q4_K_M.gguf \ | |
| --mmproj Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-mmproj-f16.gguf \ | |
| --image your_image.jpg \ | |
| -p "Describe this image" | |
| ``` | |