100t meta -> single-task ft: installing_a_modem (task77, no-DA3); eval release

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pi_behavior_100t_meta_ft_task77_noda3/README.md

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+# PiBehavior — 100-task meta → single-task finetune: `installing_a_modem` (BEHAVIOR-1K 2026)
+
+A flow-matching vision-language-action (VLA) policy for the **BEHAVIOR-1K 2026 challenge**, finetuned from the **100-task meta checkpoint** on the single task **`installing_a_modem`** (activity index **77**). RGB-only (no DA3 depth branch).
+
+## Model
+- **Architecture:** PiBehavior (the 2025 #1 IliaLarchenko `behavior_224_rgb` architecture), pi0-style flow-matching VLA.
+  - VLM backbone: **PaliGemma (gemma_2b)** · action expert: **gemma_300m** · compute dtype **bf16**.
+  - 100-task conditioning tables (task + stage embeddings); vision backbone frozen.
+- **Init:** the **100-task meta checkpoint** (`meta100-1epoch`, step **69999**).
+- **Finetuned on 1 task:** `77` **installing_a_modem**.
+- **Recipe:** 4×H200, batch **128**, FSDP=1, **2 epochs** (20,000 steps; final checkpoint = step **19999**). LR ramp-cosine `1e-8 → 5e-5` (by 1k) `→ 1e-6` (by 20k). **qvel-fixed** norm stats (bundled), fast tokenizer from the meta checkpoint.
+- **Data:** `b1k-224x224-gop8-fixed` (224×224 RGB, GOP8), the `installing_a_modem` episodes.
+
+## Contents
+- `params/` — Orbax model parameters (bf16). Load with the openpi `PiBehaviorWeightLoader`.
+- `assets/IliaLarchenko/behavior_224_rgb/` — **`norm_stats.json`** (qvel-fixed) + **`fast_tokenizer/`**. Required for eval.
+- (Optimizer `train_state` is NOT included — inference/eval release.)
+
+## Inputs / Outputs
+**Observation (input):** 3 RGB views (`base_0_rgb`, `left_wrist_0_rgb`, `right_wrist_0_rgb`, each 224×224×3 uint8) + `state` (32 float, normalize with `norm_stats["state"]`) + `prompt` (tokenized by the bundled fast tokenizer) + `task_index` = **77**.
+
+**Action (output):** `action` = **32-dim × 30-step** chunk (horizon 30), flow-sampled then **de-normalized with `norm_stats["actions"]`**. Meaningful dims (23 of 32): base vel (3), trunk (4), left arm (7), right arm (7), grippers (2).
+
+## How to evaluate (properly)
+1. **Load** `params/` with the `pi_behavior` config (`num_tasks=100`, gemma_2b + gemma_300m, `da3=None`).
+2. **Assets:** point `assets_base_dir` at the bundled `assets/` (these **qvel-fixed** `norm_stats.json` + `fast_tokenizer`) — do **not** substitute upstream/2025 norm stats.
+3. **Per step:** 3 RGB views + `state` (normalized) + `prompt` + `task_index=77`; sample the 30-step chunk (10–15 flow steps), de-normalize, execute (receding-horizon).
+4. **Benchmark:** BEHAVIOR-1K sim on **installing_a_modem**; report task **success rate**. Single-task specialist — evaluate only task 77.
+
+## Notes
+- RGB-only baseline (no GT-depth / DA3). Its DA3 counterpart is a separate checkpoint.

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pi_behavior_100t_meta_ft_task77_noda3/params/array_metadatas/process_0

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