Add paper/demo links to model card

README.md

@@ -1,47 +1,52 @@
----
-language:
-- en
-license: mit
-tags:
-- awareliquid
-- mt-lnn
-- liquid-neural-network
-- research
-pipeline_tag: text-generation
----
-
-# 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 — 60,000-step checkpoint.
-
-## Measured
-
-| Milestone | val PPL (byte-level, WikiText-103) |
-|---|---|
-| 10K steps (feasibility) | 4.53 |
-| 30K steps | 2.73 |
-| **60K steps (this checkpoint)** | **2.556** |
-
-Context-flat: PPL 2.72 / 2.72 / 2.68 at seq 128 / 256 / 512 (no length degradation).
-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.weight` is 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).
+---
+language:
+- en
+license: mit
+tags:
+- awareliquid
+- mt-lnn
+- liquid-neural-network
+- research
+pipeline_tag: text-generation
+---
+
+# 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 — 60,000-step checkpoint.
+
+## Measured
+
+| Milestone | val PPL (byte-level, WikiText-103) |
+|---|---|
+| 10K steps (feasibility) | 4.53 |
+| 30K steps | 2.73 |
+| **60K steps (this checkpoint)** | **2.556** |
+
+Context-flat: PPL 2.72 / 2.72 / 2.68 at seq 128 / 256 / 512 (no length degradation).
+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.weight` is 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).
+
+## Papers
+
+- MT-LNN architecture paper (PDF): https://huggingface.co/EverestAn/MT-LNN/resolve/main/mt_lnn_arxiv.pdf
+- 中文版: https://huggingface.co/EverestAn/MT-LNN/resolve/main/mt_lnn_arxiv_zh.pdf