Cards: drop inline comments, cross-model asides, '(chat, paper-filtered)', trust_remote_code clause; remove em dashes

README.md

@@ -16,16 +16,16 @@ tags:
 
 5B K-5-bounded base model (pretraining only).
 
-Part of the **LittleLearner** scale-up study (*pedagogically-controlled knowledge exposure*): Qwen3 dense LMs trained on a corpus filtered to U.S. K–5 material (**bounded**) vs an unfiltered FineWeb-Edu corpus (**unbounded**), to measure what an interpretable knowledge boundary costs and grants.
+Part of the **LittleLearner** scale-up study (*pedagogically-controlled knowledge exposure*): Qwen3 dense LMs trained on a corpus filtered to U.S. K-5 material (**bounded**) vs an unfiltered FineWeb-Edu corpus (**unbounded**), to measure what an interpretable knowledge boundary costs and grants.
 
 ## Model
-- **Architecture:** Qwen3 dense (`Qwen3ForCausalLM`) — standard `transformers`, no custom code / `trust_remote_code`.
-- **Size:** 5.04B params — hidden 3072, 44 layers, 24 query / 8 KV heads, FFN 9216. **Context:** 4096.
+- **Architecture:** Qwen3 dense (`Qwen3ForCausalLM`).
+- **Size:** 5.04B params, hidden 3072, 44 layers, 24 query / 8 KV heads, FFN 9216. **Context:** 4096.
 - **Tokenizer:** custom 64k byte-level BPE with per-digit splitting (ChatML special tokens).
-- **Pretraining:** 88B tokens on K-5 **LittleCurriculum** (FineWeb-Edu filtered to U.S. grades K–5). WSD schedule, sharded Muon, MXFP8, Megatron-Core on 8×B200.
+- **Pretraining:** 88B tokens on K-5 **LittleCurriculum** (FineWeb-Edu filtered to U.S. grades K-5). WSD schedule, sharded Muon, MXFP8, Megatron-Core on 8xB200.
 
 ## Evaluation
-- In-domain bits-per-byte (BPB): **0.536** (vs the 2B nanochat reference 0.805).
+- In-domain bits-per-byte (BPB): **0.536**.
 
 ## Usage
 ```python