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
+  - libero
+  - manipulation
+  - qwen-vl
+---
+
+# SemanticVLA · LIBERO
+
+> 🚧 **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 the [LIBERO](https://github.com/Lifelong-Robot-Learning/LIBERO) benchmark.
+
+## Headline result
+
+| Suite | Success rate |
+|---|---:|
+| `libero_spatial` | 0.988 |
+| `libero_object`  | 0.996 |
+| `libero_goal`    | 0.986 |
+| `libero_10`      | 0.966 |
+| **4-suite mean** | **0.9840** |
+
+Best configuration: `TL_saembs_lw010` (trace + latent semantic output, `sa_embs` injection, LM loss weight 0.10, step 30000).
+
+## Architecture
+
+- **Backbone**: Qwen2.5-VL-3B (with trace + latent-action semantic heads)
+- **Action head**: GR00T-style flow-matching expert (continuous action chunks)
+- **LAM tokenizer**: [`SemanticVLA-LAM` → `libero/v5`](https://huggingface.co/spikefly/SemanticVLA-LAM)
+- **Action horizon**: 16
+
+## Planned layout
+
+```
+SemanticVLA-LIBERO/
+├── tl-saembs-lw010-best/
+│   ├── pytorch_model.pt
+│   ├── config.yaml
+│   └── model_card.md
+└── README.md
+```
+
+Additional ablation variants (`L_none_lw010`, `TL_none_lw010`, `TL_saembs_lw005`, etc.) may be uploaded as additional subdirectories upon release.
+
+## Sibling SemanticVLA checkpoint repos
+
+| Repo | Purpose |
+|---|---|
+| 🤗 [`SemanticVLA-LAM`](https://huggingface.co/spikefly/SemanticVLA-LAM) | LAM tokenizers used by this VLA |
+| 🤗 [`SemanticVLA-Bridge`](https://huggingface.co/spikefly/SemanticVLA-Bridge) | Bridge-finetuned VLA for SimplerEnv WidowX |
+
+## Related resources
+
+- **Code**: https://github.com/Fei-Ni/SemanticVLA_Offcial
+- **Datasets**: 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-LIBERO",
+    filename="tl-saembs-lw010-best/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{liu2023libero,
+  title     = {LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning},
+  author    = {Liu, Bo and Zhu, Yifeng and others},
+  booktitle = {NeurIPS Datasets and Benchmarks},
+  year      = {2023}
+}
+```
+
+## License
+
+Released under the [MIT License](https://github.com/Fei-Ni/SemanticVLA_Offcial/blob/main/LICENSE).