Update the model card

README.md

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+---
+license: apache-2.0
+base_model: convaiinnovations/laya
+library_name: sima-lmm
+tags:
+- sima.ai
+- modalix
+- mla
+- edge
+- decision-model
+- modernbert
+---
+
+# Laya decision models, compiled for the SiMa.ai MLSoC Modalix
+
+[Laya](https://github.com/NandhaKishorM/laya) by Convai Innovations is a "System-1" decision
+model: an encoder (ModernBERT-large, or mmBERT-base for the multilingual one) with a decision
+head that answers a typed question about a piece of text in one forward pass. It picks one of
+several options, scores on a scale, or says yes or no.
+
+These are those checkpoints compiled for the Modalix MLA. Every graph is a single MLA stage,
+with no layers on the CPU, and a decision takes about 19 ms at 128 tokens (8 ms for the
+multilingual model).
+
+| folder | model | precision | latency per decision, by tokens | same decision as PyTorch | size |
+|---|---|---|---|---|---|
+| `general-int8` | Laya INT8 | A_BF16_W_INT8 | 128: 14 ms | 98 / 100 | 0.67 GB |
+
+Latency is one decision on a Modalix DevKit, measured inside the runtime. "Same decision" is
+against the fp32 PyTorch model on 100 decisions with the 128-token graph. Precision `BF16` is
+weights and activations in bfloat16; `A_BF16_W_INT8` keeps bfloat16 activations and stores
+the weights as int8.
+
+## What is in a folder
+
+| file | what it is |
+|---|---|
+| `laya_s<N>_stage1_mla.elf` | the compiled graph for sequences of up to N tokens |
+| `token_embeddings.bf16` | the embedding table, looked up on the CPU |
+| `act_tail.f32` | the last layer of the act head, run on the CPU |
+| `tokenizer.json` | the checkpoint's tokenizer |
+| `laya_config.json` | token ids, calibration temperatures, and which graphs there are |
+
+`models.json` lists every folder with file sizes and SHA-256 sums.
+
+## Using them
+
+The files run on a Modalix board with the runtime and web app from
+[sima-laya](https://github.com/dotimothy/sima-laya): its Models page downloads a model from
+this repository onto the board and loads it on the MLA. By hand:
+
+```bash
+hf download TDoSiMa/sima-laya --include "general/*" --local-dir .
+./laya run general --state "We were billed twice for March." \
+    --question '{"type": "noul", "instructions": "Is this a billing problem?"}'
+```
+
+They are not usable with PyTorch or ONNX Runtime; for that, use the original checkpoints at
+[convaiinnovations/laya](https://huggingface.co/convaiinnovations/laya).
+
+## License and attribution
+
+Apache-2.0. The models are Convai Innovations' Laya checkpoints
+(https://github.com/NandhaKishorM/laya, Apache-2.0), compiled without retraining. The
+exception is `dino`, whose decision head was fine-tuned on top of the English checkpoint for
+a browser game. Zero-shot quality is the checkpoints': the port reproduces PyTorch's answers,
+including its wrong ones.