Model card: finetune relation, no "expert" wording; demo video for the preview widget

.gitattributes

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 *tfevents* filter=lfs diff=lfs merge=lfs -text
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README.md

@@ -1,6 +1,7 @@
 ---
 license: apache-2.0
 base_model: RenzKa/simlingo
+base_model_relation: finetune
 pipeline_tag: robotics
 language:
   - en
@@ -100,7 +101,7 @@ OUT_DIR=/tmp/personadrive_route00 \
 bash scripts/eval/test_one_lb1_route.sh
 ```
 
-- **Style:** set `PERSONADRIVE_ICL_PROFILE` to `fast` (aggressive), `default` (neutral), `slow` (conservative) or `normal` (no style; the PDM-lite expert index). `PERSONADRIVE_NUM_ICL=0` turns retrieval off.
+- **Style:** set `PERSONADRIVE_ICL_PROFILE` to `fast` (aggressive), `default` (neutral, normal driving), `slow` (conservative) or `normal` (no style; the index built from SimLingo's PDM-lite data). `PERSONADRIVE_NUM_ICL=0` turns retrieval off.
 - **Retrieval data:** retrieval needs three things:
   - the retrieval head, included in the code repository;
   - the FAISS indices under `persona_drive_rag/`;
@@ -131,8 +132,8 @@ From conservative to aggressive, speed rises by 19.8 % and acceleration by 24.9
 
 - **Data:**
   - 2,848 PDM-lite routes;
-  - 350 expert routes in the aggressive style (`fast/lb1_split`);
-  - 350 expert routes in the conservative style (`slow/lb1_split`).
+  - 350 routes recorded in the aggressive style (`fast/lb1_split`);
+  - 350 routes recorded in the conservative style (`slow/lb1_split`).
 
   Each frame is paired with its K = 2 context points, retrieved from the index of the matching style.
 - **Settings:** LoRA on the language model (r 32, α 64, dropout 0.1) with the vision encoder frozen. AdamW at lr 3e-5 (OneCycle, weight decay 0.1); batch 6 per GPU × 4 GPUs with DeepSpeed ZeRO-2 in bf16; 1 epoch.

replay.mp4

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