---
language:
- en
library_name: candle
tags:
- text-generation
- from-scratch
- rust
- transformer
---

# picochat

A 90M parameter GPT trained from scratch in Rust using the [picochat](https://github.com/Nu11ified/picochat) framework.

## Model details

- **Architecture**: Decoder-only transformer with grouped-query attention, RoPE, sliding window attention, ReLU-squared MLP
- **Parameters**: 31.5M (depth=8: 8 layers, 512 dim, 8 heads, 4 KV heads)
- **Vocab size**: 4,096 (BPE tokenizer)
- **Context length**: 2048 tokens
- **Training**: Pretrained on OpenWebText (10k steps), then supervised fine-tuned on UltraChat + no_robots (2k steps)
- **Framework**: [candle](https://github.com/huggingface/candle) (Rust)
- **Trained on**: CPU only

## Usage

```bash
# Clone the framework
git clone https://github.com/Nu11ified/picochat.git
cd picochat

# Download weights
mkdir -p runs/model
# Download model.safetensors, config.json, and tokenizer.json from this repo
# into runs/model/

# Chat
cargo run --release -- \
  --chat --load runs/model --tokenizer runs/model/tokenizer.json \
  --temperature 0.8 --max-tokens 256

# Web UI
cargo run --release -- \
  --serve --load runs/model --tokenizer runs/model/tokenizer.json --port 8000
```

## Limitations

This model was trained on CPU with limited data (~5M tokens vs GPT-2's 8B). It produces coherent text on topics seen during training but will generate garbled output on novel questions. The value of this project is the from-scratch Rust training framework, not the resulting model.

## Files

- `model.safetensors` -- model weights (120MB)
- `config.json` -- model architecture config
- `tokenizer.json` -- BPE tokenizer (32K vocab)