Text-to-Video
Diffusers
Safetensors
Transformers
English
Chinese
image-to-video
video-continuation
Eval Results
Instructions to use meituan-longcat/LongCat-Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use meituan-longcat/LongCat-Video with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("meituan-longcat/LongCat-Video", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Transformers
How to use meituan-longcat/LongCat-Video with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("meituan-longcat/LongCat-Video", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Add WBench evaluation results
Browse files- .eval_results/wbench.yaml +14 -0
.eval_results/wbench.yaml
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- dataset:
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id: meituan-longcat/WBench
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task_id: wbench_navi
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value: 73.7
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source:
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url: https://meituan-longcat.github.io/WBench/
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name: WBench Leaderboard
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- dataset:
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id: meituan-longcat/WBench
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task_id: wbench_full
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value: 69.9
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source:
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url: https://meituan-longcat.github.io/WBench/
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name: WBench Leaderboard
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