# Bonsai 1.7B (1-Bit Quantized)

Bonsai 1.7B is an experimental 1-bit quantized Large Language Model. It uses a specialized `Q1_0_g128` format that achieves approximately 1.125 bits per parameter.

## Model Details

- **Parameters**: 1.7 Billion
- **Format**: `.cellm` (Cellm binary format)
- **Quantization**: 1-bit sign-magnitude with 16-bit group scales (g128)
- **Size**: 231 MB
- **Base Architecture**: Qwen2-style Transformer

## Usage in Cellm

To run inference using the Cellm CLI:

```bash
./target/release/infer \
  --model Bonsai-1.7B_v2.cellm \
  --tokenizer tokenizer.json \
  --prompt "What is sycophancy?" \
  --backend metal \
  --gen 100
```

## Performance Note

This model is optimized for extremely low-memory environments. At 231MB, it can run on devices with very limited RAM. While the quantization is aggressive, it maintains coherent English generation for simple prompts.

## Implementation Analysis

For a detailed technical breakdown of how the 1-bit quantization works and how it was implemented in cellm, see the [Bonsai 1-Bit Analysis](https://github.com/jeffasante/cellm/blob/main/docs/bonsai_1bit_analysis.md).