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q-future
/
one-align

Zero-Shot Image Classification
Transformers
PyTorch
mplug_owl2
feature-extraction
custom_code
Model card Files Files and versions
xet
Community
7

Instructions to use q-future/one-align with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use q-future/one-align with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="q-future/one-align", trust_remote_code=True)
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("q-future/one-align", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Fix SDPA & Flash-Attention

#7 opened 11 months ago by
Agnellino

how to calculate the score with batch?

#6 opened over 1 year ago by
Phoenix1551

Adding `safetensors` variant of this model

#5 opened over 1 year ago by
SFconvertbot

Removing the if __name__ == "__main__" part which (if I am not mistaken) would never be used in this scenario.

#4 opened about 2 years ago by
fboeEl

remove unnecessary import of ice cream

#3 opened about 2 years ago by
fboeEl

Adding `safetensors` variant of this model

#2 opened about 2 years ago by
SFconvertbot

How to use video evaluation?

#1 opened about 2 years ago by
gauravsaha
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