lattice-research/lattice-quark-1.5b-mlx

Lattice Quark 1.5B (MLX 4-bit)

MLX conversion of the Quark 1.5B nanochat-style language model, trained from scratch. Optimized for Apple Silicon: transformer linears quantized to 4-bit (group size 64), token and value embeddings kept in bf16.

• Parameters: 1.5B (total, incl. value embeddings)
• Layers: 26, hidden 1536, 12 heads, head dim 128
• Context: 2048 tokens, RoPE base 100k
• Vocab: 32768 (GPT-4-style BPE)
• Model type: nanochat2 (complete architecture: value embeddings, smear, backout, residual lambdas)
• Size: ~1.7GB

Files

• model.safetensors — weights (4-bit quantized linears + bf16 embeddings)
• config.json — model configuration (model_type: nanochat2)
• tokenizer.json / tokenizer_config.json — HuggingFace tokenizer (byte-exact with the training tokenizer, incl. chat template)
• nanochat_tokenizer.json — original tokenizer dump
• nanochat_rope.safetensors — precomputed rotary embeddings
• generation_config.json — eos = <|assistant_end|> (32763)

Usage

Requires the nanochat2 model type, available since mlx-lm PR #1761:

pip install mlx-lm
mlx_lm.generate --model lattice-research/lattice-quark-1.5b-mlx --prompt "what are you"

The chat template wraps prompts in the SFT marker format from training.

Source

Base checkpoint: lattice-research/lattice-quark-1.5b