M2-2B
1.93B-parameter AwareLiquid M2 preset (2080 width × 34 layers × 16 heads),
the M2 experimental line's 2b configuration trained via m2_training.
Byte-level tokenizer (UTF-8 bytes, vocab 256).
Status at upload: research milestone — first complete 30,000-step run.
Measured
| Milestone | val PPL (byte-level, WikiText-103) |
|---|---|
| 10K steps (feasibility) | 4.53 |
| 30K steps (this checkpoint) | 2.73 |
≈ 1.45 BPB. Training: bf16 model, AdamW8bit, lr 1e-4, seq 128, batch 8 × grad_accum 4, on a single A100-PCIE-40GB.
Boundaries (honest)
- Byte-level, not a subword model — PPL is on UTF-8 byte tokens; NOT comparable to gpt2-vocab models. Serve with byte tokenization.
- Not an instruct/chat model — raw next-token pretraining only.
- Research checkpoint — bf16 safetensors (weight-tied embedding; the tied
lm_head.weightis omitted, standard HF re-tie on load). No optimizer state: not exactly resumable. - The M2 line's verdict so far is honest-null on reasoning mechanisms; this checkpoint is the language-line scaling artifact, not a capability claim.
Config
config.json carries the full MTLNNConfig (d_model 2080, 34 layers, 16 heads,
gwtb_n_heads=1, vocab 256, max_seq_len 129).
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