| --- |
| license: mit |
| base_model: AAyano/oft_setting2_chunksize25_batch32_20k |
| tags: |
| - robotics |
| - vla |
| - openvla |
| - openvla-oft |
| - xarm |
| - task-conditioned-gate |
| library_name: transformers |
| --- |
| |
| # gate_setting2_chunksize25_batch32_from20000 |
|
|
| Task-conditioned **text-token-gate** OpenVLA-OFT model for real-world XArm, **setting 2: cup stacking**. |
| Trained fresh for **10000 steps** on top of the [oft_setting2_chunksize25_batch32_20k](https://huggingface.co/AAyano/oft_setting2_chunksize25_batch32_20k) OFT backbone (action head / proprio projector / FiLM re-trained; cosine LR 5e-4 with 1000 warmup, effective batch 32, seed 6). |
|
|
| ## Gate configuration (baked into `config.json`) |
|
|
| - Gazing: `self_attention` (dim 512, 8 heads, 1 layer), gate MLP hidden 512 / depth 1 |
| - Text pooling: `contrastive_alignment_score` (visual τ 0.1, text τ 0.05), instruction-only pooling, stopword filtering |
| - Layer gate: `threshold` mode, threshold 0.3, strength 0.5 |
| - Budget loss: target 0.4, weight 0.01 |
|
|
| ## ⚠️ Serving requires the Task-conditioned_Gate codebase |
| |
| The gate modules live in this repo's `modeling_prismatic.py` (loaded via `trust_remote_code`), but the openvla-oft serve flow syncs the local repo's modeling files INTO the checkpoint before loading. Serve with `REPO_DIR` pointing at the [Task-conditioned_Gate](https://github.com/Kaixi66/Task-conditioned_Gate) repo — serving with vanilla openvla-oft silently drops the gate weights. |
| |
| ## Contents |
| |
| - Merged full model (`model-*.safetensors`, gate config in `config.json`) |
| - `lora_adapter/` — LoRA + gate weights (`modules_to_save=["text_token_gate"]`), standalone copy |
| - `action_head--10000_checkpoint.pt`, `proprio_projector--10000_checkpoint.pt`, `vision_backbone--10000_checkpoint.pt` (FiLM) |
| - `dataset_statistics.json`, `oft_training_config.json` (chunk 25, action dim 7, proprio dim 6, BOUNDS_Q99) |
| |
