# Tiny model - small but trainable (~9M params)
# Good for quick experiments and testing

attention tiny_attn {
    num_heads: 4
    bias: false
}

ffn tiny_ffn {
    hidden_dim: 512
    activation: gelu
    bias: false
}

block tiny_block {
    attention: tiny_attn
    ffn: tiny_ffn
    norm: rmsnorm { eps: 1e-5 }
    norm_position: pre
    residual: true
}

model tiny {
    description: "Small model for quick experiments"
    vocab_size: 32000
    max_seq_len: 512
    hidden_size: 128
    num_layers: 4
    block: tiny_block
}
