Text Generation
GGUF
Safetensors
qwen3
ternary
1.58-bit
apple-silicon
on-device
prismml
bonsai
conversational
2-bit
Instructions to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered", filename="Bonsai-REDUX2-altered-Q2_K.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K # Run inference directly in the terminal: llama-cli -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K # Run inference directly in the terminal: llama-cli -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
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 jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K # Run inference directly in the terminal: ./llama-cli -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
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 jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
Use Docker
docker model run hf.co/jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
- LM Studio
- Jan
- vLLM
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
- Ollama
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with Ollama:
ollama run hf.co/jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
- Unsloth Studio
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered 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 jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered 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 jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered to start chatting
- Pi
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
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": "jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
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 jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
Run Hermes
hermes
- Docker Model Runner
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with Docker Model Runner:
docker model run hf.co/jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
- Lemonade
How to use jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jinreiyu/Bonsai-REDUX2-gguf-Q2_K-altered:Q2_K
Run and chat with the model
lemonade run user.Bonsai-REDUX2-gguf-Q2_K-altered-Q2_K
List all available models
lemonade list
| { | |
| "architectures": [ | |
| "Qwen3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": null, | |
| "dtype": "float16", | |
| "eos_token_id": 151645, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 12288, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "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" | |
| ], | |
| "max_position_embeddings": 65536, | |
| "max_window_layers": 28, | |
| "model_type": "qwen3", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 36, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 151643, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "factor": 4.0, | |
| "original_max_position_embeddings": 16384, | |
| "rope_theta": 1000000.0, | |
| "rope_type": "yarn" | |
| }, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "5.7.0", | |
| "use_cache": true, | |
| "use_sliding_window": false, | |
| "vocab_size": 151669, | |
| "quantization": { | |
| "group_size": 128, | |
| "bits": 2, | |
| "mode": "affine" | |
| }, | |
| "quantization_config": { | |
| "group_size": 128, | |
| "bits": 2, | |
| "mode": "affine" | |
| } | |
| } |