Instructions to use sinatras/qwen3.5-2b-split with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use sinatras/qwen3.5-2b-split with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="sinatras/qwen3.5-2b-split", filename="Q4_K_M/Qwen3.5-2B-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
- llama.cpp
How to use sinatras/qwen3.5-2b-split with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sinatras/qwen3.5-2b-split:Q4_K_M # Run inference directly in the terminal: llama-cli -hf sinatras/qwen3.5-2b-split:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sinatras/qwen3.5-2b-split:Q4_K_M # Run inference directly in the terminal: llama-cli -hf sinatras/qwen3.5-2b-split: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 sinatras/qwen3.5-2b-split:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf sinatras/qwen3.5-2b-split: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 sinatras/qwen3.5-2b-split:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf sinatras/qwen3.5-2b-split:Q4_K_M
Use Docker
docker model run hf.co/sinatras/qwen3.5-2b-split:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use sinatras/qwen3.5-2b-split with Ollama:
ollama run hf.co/sinatras/qwen3.5-2b-split:Q4_K_M
- Unsloth Studio
How to use sinatras/qwen3.5-2b-split 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 sinatras/qwen3.5-2b-split 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 sinatras/qwen3.5-2b-split to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sinatras/qwen3.5-2b-split to start chatting
- Pi
How to use sinatras/qwen3.5-2b-split with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf sinatras/qwen3.5-2b-split: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": "sinatras/qwen3.5-2b-split:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use sinatras/qwen3.5-2b-split with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf sinatras/qwen3.5-2b-split: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 sinatras/qwen3.5-2b-split:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use sinatras/qwen3.5-2b-split with Docker Model Runner:
docker model run hf.co/sinatras/qwen3.5-2b-split:Q4_K_M
- Lemonade
How to use sinatras/qwen3.5-2b-split with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sinatras/qwen3.5-2b-split:Q4_K_M
Run and chat with the model
lemonade run user.qwen3.5-2b-split-Q4_K_M
List all available models
lemonade list
Add files using upload-large-folder tool
Browse files- .gitattributes +3 -0
- Q4_K_M/Qwen3.5-2B-Q4_K_M.gguf +3 -0
- Q6_K/Qwen3.5-2B-Q6_K.gguf +3 -0
- README.md +24 -0
- UD-Q2_K_XL/Qwen3.5-2B-UD-Q2_K_XL.gguf +3 -0
.gitattributes
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Q4_K_M/Qwen3.5-2B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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UD-Q2_K_XL/Qwen3.5-2B-UD-Q2_K_XL.gguf filter=lfs diff=lfs merge=lfs -text
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Q6_K/Qwen3.5-2B-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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Q4_K_M/Qwen3.5-2B-Q4_K_M.gguf
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README.md
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---
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license: apache-2.0
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base_model: unsloth/Qwen3.5-2B-GGUF
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tags:
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- gguf
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- wllama
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- browser
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---
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# qwen3.5-2b-split
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Qwen3.5 2B GGUF artifacts used by the playground wllama preset.
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These files are the GGUF artifacts used by the local Transformers.js playground
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wllama CPU presets. Large files are kept under quantization subdirectories so
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browser clients can request the first shard URL and expand the remaining shards.
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## Source And License
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- Source model/artifact: [unsloth/Qwen3.5-2B-GGUF](https://huggingface.co/unsloth/Qwen3.5-2B-GGUF)
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- License: Apache-2.0, inherited from the source model/artifact.
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The GGUF conversion, quantization, and splitting steps do not change the
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upstream model license.
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UD-Q2_K_XL/Qwen3.5-2B-UD-Q2_K_XL.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:dbcf28421dece9c86884f9da5a2291c8214be7920623f1fcb663ed8f58b38ccb
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size 966533376
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