Initial placeholder model card

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README.md

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+---
+license: mit
+library_name: pytorch
+pipeline_tag: robotics
+tags:
+  - robotics
+  - vision-language-action
+  - vla
+  - bridge
+  - widowx
+  - simpler-env
+  - manipulation
+  - qwen-vl
+---
+
+# SemanticVLA · Bridge (SimplerEnv WidowX)
+
+> 🚧 **Placeholder.** The URL is stable; checkpoints will be uploaded incrementally per the [release roadmap](https://github.com/Fei-Ni/SemanticVLA_Offcial/blob/main/docs/ROADMAP.md).
+
+[SemanticVLA](https://github.com/Fei-Ni/SemanticVLA_Offcial) finetuned on [BridgeData V2](https://rail-berkeley.github.io/bridgedata/), targeting [SimplerEnv](https://github.com/simpler-env/SimplerEnv) WidowX evaluation (`widowx_spoon_on_towel` / `widowx_carrot_on_plate` / `widowx_stack_cube` / `widowx_put_eggplant_in_basket`).
+
+## Configuration
+
+| Field | Value |
+|---|---|
+| Backbone | Qwen3VL-4B (Qwen3VL-GR00T-Bridge-RT-1 init) |
+| Action head | GR00T-style flow-matching expert |
+| Semantic output | `trace_latent` (trace + LAM latent-action token), `none` injection |
+| LM loss weight | 0.10 |
+| Action horizon | 16 |
+| LAM tokenizer | [`SemanticVLA-LAM` → `oxe-bridge-only/v4-step16k`](https://huggingface.co/spikefly/SemanticVLA-LAM) |
+| Training data | `bridge_orig_1.0.0_lerobot` (with dense trace labels via OXE NPY index) |
+| Target | 100,000 steps |
+
+## Headline result
+
+SimplerEnv WidowX numbers will be filled in here once the 100k-step training and the 24-episodes-per-task evaluation complete. Training is in flight on Isambard; see the [code repo](https://github.com/Fei-Ni/SemanticVLA_Offcial) for the latest training metrics.
+
+## Planned layout
+
+```
+SemanticVLA-Bridge/
+├── tl-none-lw010-step100k/
+│   ├── pytorch_model.pt
+│   ├── config.yaml
+│   └── model_card.md
+└── README.md
+```
+
+## Sibling SemanticVLA checkpoint repos
+
+| Repo | Purpose |
+|---|---|
+| 🤗 [`SemanticVLA-LAM`](https://huggingface.co/spikefly/SemanticVLA-LAM) | LAM tokenizers used by this VLA |
+| 🤗 [`SemanticVLA-LIBERO`](https://huggingface.co/spikefly/SemanticVLA-LIBERO) | LIBERO-finetuned VLA |
+
+## Related resources
+
+- **Code**: https://github.com/Fei-Ni/SemanticVLA_Offcial
+- **Datasets · Bridge subset**: https://huggingface.co/datasets/spikefly/SemanticVLA-Bridge-LeRobot
+- **Datasets · all**: https://hf.co/collections/spikefly/semanticvla-datasets
+- **Collection · Model Zoo**: https://hf.co/collections/spikefly/semanticvla-model-zoo
+
+## How to load (placeholder API)
+
+```python
+from huggingface_hub import hf_hub_download
+import torch
+
+ckpt = hf_hub_download(
+    repo_id="spikefly/SemanticVLA-Bridge",
+    filename="tl-none-lw010-step100k/pytorch_model.pt",
+)
+state = torch.load(ckpt, map_location="cpu")
+# loader will be released with the code repo
+```
+
+## Citation
+
+```bibtex
+@misc{semanticvla2026,
+  title  = {SemanticVLA: Semantic Vision-Language-Action Models with Trace-Conditioned Latent Action Tokens},
+  author = {SemanticVLA Authors},
+  year   = {2026},
+  url    = {https://github.com/Fei-Ni/SemanticVLA_Offcial}
+}
+
+@inproceedings{walke2023bridgedata,
+  title     = {BridgeData V2: A Dataset for Robot Learning at Scale},
+  author    = {Walke, Homer and Black, Kevin and others},
+  booktitle = {Conference on Robot Learning (CoRL)},
+  year      = {2023}
+}
+```
+
+## License
+
+Released under the [MIT License](https://github.com/Fei-Ni/SemanticVLA_Offcial/blob/main/LICENSE).