Instructions to use switlydev/SysZero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use switlydev/SysZero 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 switlydev/SysZero:Q4_K_M # Run inference directly in the terminal: llama cli -hf switlydev/SysZero:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf switlydev/SysZero:Q4_K_M # Run inference directly in the terminal: llama cli -hf switlydev/SysZero: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 switlydev/SysZero:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf switlydev/SysZero: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 switlydev/SysZero:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf switlydev/SysZero:Q4_K_M
Use Docker
docker model run hf.co/switlydev/SysZero:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use switlydev/SysZero with Ollama:
ollama run hf.co/switlydev/SysZero:Q4_K_M
- Unsloth Studio
How to use switlydev/SysZero 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 switlydev/SysZero 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 switlydev/SysZero to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for switlydev/SysZero to start chatting
- Docker Model Runner
How to use switlydev/SysZero with Docker Model Runner:
docker model run hf.co/switlydev/SysZero:Q4_K_M
- Lemonade
How to use switlydev/SysZero with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull switlydev/SysZero:Q4_K_M
Run and chat with the model
lemonade run user.SysZero-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 1,582 Bytes
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"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": null,
"torch_dtype": "float16",
"eos_token_id": 151645,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 8960,
"layer_types": [
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
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"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention"
],
"max_position_embeddings": 32768,
"max_window_layers": 21,
"model_type": "qwen2",
"num_attention_heads": 12,
"num_hidden_layers": 28,
"num_key_value_heads": 2,
"pad_token_id": 151665,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 1000000.0,
"rope_type": "default"
},
"sliding_window": null,
"tie_word_embeddings": true,
"unsloth_fixed": true,
"unsloth_version": "2026.5.9",
"use_cache": false,
"use_sliding_window": false,
"vocab_size": 151936
} |