---
license: apache-2.0
task_categories:
  - video-text-to-text
  - question-answering
language:
  - en
tags:
  - world-model
  - spatial-intelligence
  - seva
  - qwen3-vl
  - vsi-bench
  - ovos-bench
  - mmsi-bench
pretty_name: WorldFold v7-enhance++ Checkpoint & Precomputed 4-Anchor SEVA World-Model Feature Caches
---

# WorldFold (`v7-enhance++`) — Model Weights & Unified 4-Anchor SEVA World-Model Feature Caches

This repository hosts the trained **`Worldfold-v7-enhance++`** adapter checkpoint and the precomputed **Stable Virtual Camera (SEVA v1.1) + Qwen3-VL-8B Visual Tower** world-model feature caches across all four training and evaluation splits (`VSI-Train-10k`, `VSI-Bench`, `OVO-S-Bench`, and `MMSI-Video-Bench`).

All four splits are **100% unified under the 4-Anchor Chronological Protocol (`four_anchor_protocol: True`)**:
- **4 Chronological Anchors (`M = 4`)** sampled at `(20%, 40%, 60%, 80%)` of the video timeline.
- **1 Canonical 3D Camera Trajectory per Anchor × 2 Rollout Steps (`T = 2`)** (`Orbit-Right`, `Orbit-Left`, `Dolly-Forward`, `Pan-Sweep`).
- **8 Generated Novel Views (`4 × 2`)**, each encoded by frozen `Qwen3-VL-8B-Instruct` visual tower and pooled to `16` patches (`[4, 2, 16, 4096]`, `bfloat16`, L2 norm `12.32`).

Codebase branch: **[`inFaaa/WorldFold` (`v7-enhance-pp`)](https://github.com/inFaaa/WorldFold/tree/v7-enhance-pp)**

---

## Included Assets

| File in Repository | Split / Role | Count | Protocol (`M × T × P × D`) | Size | Unpack / Target Path |
| :--- | :--- | :---: | :---: | :---: | :--- |
| `checkpoints/Worldfold-v7-enhance++.pt` | 2-Epoch Trained Adapter Checkpoint (`fp32`) | 1 checkpoint | `K in {256, 128, 64, 16}` | `75.5 MB` | `outputs/nested_prior_runs/spec_v7_runs/checkpoints/Worldfold-v7-enhance++.pt` |
| `vsi_eval_seva_288scenes.tar.gz` | **VSI-Bench** Test SEVA Features | `288` scenes (`5,130` QA) | `4 Anchors × 2 Steps × 16 × 4096` (`four_anchor_protocol=True`) | `549.3 MB` | Extract into `outputs/cache/vsi_eval_cache/` (`scene_feats_real_seva/*.pt`) |
| `ovos_eval_seva_339videos.tar.gz` | **OVO-S-Bench** Test SEVA Features | `339` videos (`1,695` QA) | `4 Anchors × 2 Steps × 16 × 4096` (`four_anchor_protocol=True`) | `551.6 MB` | Extract into `outputs/cache/ovos_eval_cache/` (`real_seva_feats/*.pt`) |
| `mmsi_eval_seva_1106questions.tar.gz` | **MMSI-Video-Bench** Test SEVA Features | `1,106` questions | `4 Anchors × 2 Steps × 16 × 4096` (`four_anchor_protocol=True`) | `1.84 GB` | Extract into `outputs/cache/mmsi_eval_cache/` (`real_seva_feats/question_*.pt`) |
| `vsi_train10k_seva_only_3449scenes.pt` | **VSI-Train-10k** Training SEVA Features | `3,449` scenes (`10,169` QA) | `4 Anchors × 2 Steps × 16 × 4096` (`four_anchor_protocol=True`) | `8.26 GB` | Packed dict `{scene_key: {wm_4x2, real_4x2, anchor_context, real_context, metadata}}` |

---

## Quick Download & Unpack

```bash
pip install -U huggingface_hub

# Download all checkpoints and SEVA caches
hf download Jinfa/WorldFold-v7-Cache --repo-type dataset --local-dir ./WorldFold-v7-Cache

# Unpack the 3 evaluation benchmark SEVA caches
mkdir -p outputs/cache/vsi_eval_cache outputs/cache/ovos_eval_cache outputs/cache/mmsi_eval_cache
tar -xzf ./WorldFold-v7-Cache/vsi_eval_seva_288scenes.tar.gz -C outputs/cache/vsi_eval_cache/
tar -xzf ./WorldFold-v7-Cache/ovos_eval_seva_339videos.tar.gz -C outputs/cache/ovos_eval_cache/
tar -xzf ./WorldFold-v7-Cache/mmsi_eval_seva_1106questions.tar.gz -C outputs/cache/mmsi_eval_cache/
```