Update README.md

README.md

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 ---
 license: apache-2.0
+library_name: diffusers
+pipeline_tag: robotics
+tags:
+  - robotics
+  - world-model
+  - video-generation
+  - vision-action
+  - next-forcing
+  - robotwin
 ---
+
+# Next Forcing — RoboTwin Post-trained Checkpoint
+
+Post-trained checkpoint for **Next Forcing: Causal World Modeling with
+Multi-Chunk Prediction**, evaluated on the RoboTwin 2.0 benchmark.
+
+- 📄 Paper: https://arxiv.org/pdf/2606.11187
+- 🌐 Project page: https://gangweix.github.io/next-forcing/
+- 💻 Code: https://github.com/gangweix/next-forcing
+
+## Model Description
+
+Next Forcing addresses the myopic supervision problem in autoregressive video
+world models: next-chunk denoising tends to learn local appearance shortcuts
+instead of long-range dynamics, especially at high frame rates. Lightweight
+**Multi-Chunk Prediction (MCP)** modules predict multiple future chunks through
+a causal chain during training, providing dense temporal supervision to the
+backbone.
+
+This checkpoint is the RoboTwin post-trained model, built on top of the
+[LingBot-VA](https://github.com/Robbyant/lingbot-va) codebase. It was post-trained
+from [`gangweix/next-forcing-base`](https://huggingface.co/gangweix/next-forcing-base).
+
+| | |
+| --- | --- |
+| Parameters | 6.7B (BF16) |
+| Backbone layers | 30 |
+| MCP depths | 3 (`mcp_blocks_per_depth=3`, collect layers `[3, 11, 19, 29]`) |
+| Benchmark | RoboTwin 2.0, 50 bimanual manipulation tasks |
+| Initialized from | [`next-forcing-base`](https://huggingface.co/gangweix/next-forcing-base) (5.1B) |
+
+## Results
+
+Average success rate on RoboTwin 2.0:
+
+| Setting | LingBot-VA | **Next Forcing** |
+| --- | ---: | ---: |
+| Clean | 92.9 | **94.1** |
+| Random | 91.5 | **93.5** |
+
+## Repository Layout
+
+```text
+transformer/     Next Forcing backbone with MCP modules (enable_mcp=true)
+vae/
+text_encoder/
+tokenizer/
+```
+
+## Usage
+
+Clone the code and install the dependencies as described in the
+[repository README](https://github.com/gangweix/next-forcing).
+
+```bash
+python -m pip install "huggingface_hub[cli]"
+hf download gangweix/next-forcing-posttrain-robotwin \
+  --local-dir ./checkpoints/next-forcing-posttrain-robotwin
+```
+
+The evaluation code resolves model subfolders by path, so point
+`NEXT_FORCING_MODEL_PATH` at the **local directory**, not at the Hub repository
+id:
+
+```bash
+export NEXT_FORCING_MODEL_PATH=$PWD/checkpoints/next-forcing-posttrain-robotwin
+export ROBOTWIN_ROOT=/path/to/your/RoboTwin
+
+# Start the inference server on one GPU
+CUDA_VISIBLE_DEVICES=0 bash evaluation/robotwin/launch_server.sh
+
+# In another terminal, evaluate one task for 100 trials
+bash evaluation/robotwin/launch_client.sh /path/to/eval_results adjust_bottle
+```
+
+RoboTwin evaluation requires a working RoboTwin 2.0 installation; see the
+[official guide](https://robotwin-platform.github.io/doc/usage/robotwin-install.html).
+
+## License
+
+Released under the Apache License 2.0. Next Forcing is developed on top of the
+LingBot-VA codebase; please retain the upstream attribution and license when
+redistributing.
+
+## Citation
+
+```bibtex
+@article{xu2026next,
+  title={Next Forcing: Causal World Modeling with Multi-Chunk Prediction},
+  author={Xu, Gangwei and Zhang, Qihang and Zhou, Jiaming and Zhu, Xing and Shen, Yujun and Yang, Xin and Xu, Yinghao},
+  journal={arXiv preprint arXiv:2606.11187},
+  year={2026}
+}
+```