---
title: LoomVideo-train
canonical_url: "https://www.modelscope.cn/models/yansongwei/LoomVideo-train"
md_url: "https://www.modelscope.cn/models/yansongwei/LoomVideo-train.md"
repository: yansongwei/LoomVideo-train
last_updated: 2026-08-17
pipeline_tag: text-generation
tasks:
  - text-generation
library_name:
  - pytorch
frameworks:
  - pytorch
downloads: 0
stars: 0
---

# LoomVideo-train

> LoomVideo-train - yansongwei 在 ModelScope 开源的模型。LoRA checkpoints fine-tuned for realistic traffic-accident video generation and editing on CAP data. Only inference-relevant adapter weights and resolved configuration files are published; datasets, ordinary…

- **Repository**: yansongwei/LoomVideo-train
- **Tasks**: text-generation
- **Downloads**: 0
- **Stars**: 0
- **Last updated**: 2026-08-17

Source: https://www.modelscope.cn/models/yansongwei/LoomVideo-train

---

# LoomVideo CAP LoRA

LoRA checkpoints fine-tuned for realistic traffic-accident video generation
and editing on CAP data. Only inference-relevant adapter weights and resolved
configuration files are published; datasets, ordinary logs, smoke-test
checkpoints, generated videos, and evaluation outputs are excluded.

## Base components

- LoomVideo pretrained checkpoint
- Wan2.2-TI2V-5B-Diffusers generator backbone
- Qwen3-VL-8B-Instruct understanding model

The matching base checkpoints are required for inference.

## Training configuration

- Training steps: 3,200
- Checkpoint interval: 400 steps
- Gradient accumulation steps: 1
- Learning rate: 1e-4
- LoRA rank: 16
- LoRA alpha: 16
- LoRA dropout: 0.05
- Target modules: `to_q`, `to_k`, `to_v`, `to_out.0`
- LoRA parameters: 23,592,960
- Saved dtype: BF16
- Frames per clip: 32
- Training FPS: 24
- Resolution bucket: 640
- Seed: 0

## Checkpoints

The repository includes checkpoints for steps 400, 800, 1200, 1600, 2000,
2400, 2800, and 3200. Each `lora.pth` contains 480 LoRA tensors. The final
adapter is:

`checkpoints/step-3200/lora.pth`