Instructions to use YuRiVeRTi/V2Q with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YuRiVeRTi/V2Q with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YuRiVeRTi/V2Q", dtype=torch.bfloat16, device_map="cuda") prompt = "Paris is the <mask> of France." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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license: mit
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license: mit
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datasets:
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- Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT
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language:
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- en
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metrics:
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- bertscore
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base_model:
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- Qwen/QwQ-32B
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pipeline_tag: fill-mask
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library_name: diffusers
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