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@@ -81,12 +81,12 @@ We define a high-quality video dataset based on two core principles: (1) No cont
| LLaVA-1.6-34B | 141.75851073472666 | 472 | 48.52492072346965 |
### Training Diffusion Model
Similar to previous work, we employ a multi-stage cascaded training approach, which consumes a total of 2,048 A800 GPU hours. We found that joint training with images significantly accelerates model convergence and enhances visual perception, aligning with the findings of [Latte](https://github.com/Vchitect/Latte). Below is our training card:
Similar to previous work, we employ a multi-stage cascaded training approach, which consumes a total of 2,528 A800 GPU hours. We found that joint training with images significantly accelerates model convergence and enhances visual perception, aligning with the findings of [Latte](https://github.com/Vchitect/Latte). Below is our training card:
| Name | Stage 1 | Stage 2 | Stage 3 | Stage 4 |
|---|---|---|---|---|
| Training Video Size | 17×256×256 | 65×256×256 | 65×512×512 | 65×1024×1024 |
| Compute (#A800 GPU x #Hours) | 32 × 40 | 32 × 18 | 32 × 6 | Under training |
| Compute (#A800 GPU x #Hours) | 32 × 40 | 32 × 22 | 32 × 17 | Under training |
| Checkpoint | [HF](https://huggingface.co/LanguageBind/Open-Sora-Plan-v1.0.0/tree/main/17x256x256) | [HF](https://huggingface.co/LanguageBind/Open-Sora-Plan-v1.0.0/tree/main/65x256x256) | [HF](https://huggingface.co/LanguageBind/Open-Sora-Plan-v1.0.0/tree/main/65x512x512) | Under training |
| Log | [wandb](https://api.wandb.ai/links/linbin/p6n3evym) | [wandb](https://api.wandb.ai/links/linbin/t2g53sew) | [wandb](https://api.wandb.ai/links/linbin/uomr0xzb) | Under training |
| Training Data | ~40k videos | ~40k videos | ~40k videos | ~40k videos |