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README.md

@@ -1,3 +1,70 @@
 ---
 license: apache-2.0
+base_model: MINT-SJTU/Evo1_LIBERO
+tags:
+  - vla
+  - vision-language-action
+  - robotics
+  - gguf
+  - vla.cpp
+  - llama.cpp
+  - libero
+  - evo1
+pipeline_tag: robotics
+library_name: vla.cpp
 ---
+
+# Evo-1 — LIBERO (GGUF for vla.cpp)
+
+GGUF conversion of [`MINT-SJTU/Evo1_LIBERO`](https://huggingface.co/MINT-SJTU/Evo1_LIBERO)
+for inference with [**vla.cpp**](https://github.com/VinRobotics/vla.cpp), a lightweight
+C++ inference engine for Vision-Language-Action models built on top of
+[`llama.cpp`](https://github.com/ggml-org/llama.cpp).
+
+Evo-1 couples an **InternVL3-1B** vision-language backbone with a
+**cross-attention DiT** flow-matching action head. Its vision tower is baked into
+the combined GGUF, so **no separate mmproj file is needed**.
+
+## Files
+
+| File | Size | Description |
+|---|---:|---|
+| `evo1-libero.gguf` | 1.45 GiB | Combined VLA model — InternVL3 LM + vision tower + cross-attn DiT action head + dataset stats + arch config, BF16 |
+
+## Usage
+
+```bash
+# Terminal 1 — serve (use the CUDA build for inference). No mmproj argument.
+./build-cuda/vla-server --bind tcp://*:5566 \
+    evo1-libero.gguf
+
+# Terminal 2 — drive a LIBERO episode (inside the LIBERO uv venv)
+python eval/client/run_sim_client_direct.py \
+    --arch evo1 \
+    --task libero_object --task-id 0 --n-episodes 10 \
+    --vla-addr tcp://localhost:5566
+```
+
+## Benchmark
+
+Full `libero_object` sweep (10 tasks × 20 episodes = 200 episodes):
+
+| Hardware | n_act | Success rate | client/step | client/call | Peak mem |
+|---|---:|---:|---:|---:|---:|
+| RTX 3060 (sm_86) | 8 | 94.5% | 63.60 ms | 509 ms | 1564 MiB VRAM |
+| Jetson AGX Orin (sm_87) | 8 | 95.5% | 131.01 ms | 1048 ms | 638 MiB RAM |
+| Jetson Orin Nano 8 GB (sm_87) | 8 | 97.5% | 458.84 ms | 3671 ms | 2135 MiB RAM |
+
+## Implementation note
+
+Evo-1 exposed a Qwen2 + flash-attention-2 masking subtlety: HF's FA2 path zeroes
+the attention output of masked queries, while a naïve softmax computes real
+attention for them — contaminating the LM context at image-context positions.
+vla.cpp mirrors HF exactly with a per-query mask, which is what takes this
+checkpoint from 0/5 to passing on LIBERO.
+
+## License
+
+Weights follow the upstream license of
+[`MINT-SJTU/Evo1_LIBERO`](https://huggingface.co/MINT-SJTU/Evo1_LIBERO). The
+vla.cpp conversion tooling and inference engine are MIT-licensed.