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
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pipeline_tag: zero-shot-image-classification
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## Quick Start with AutoModel
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For this image,  start an AutoModel scorer with `transformers==4.36.1`:
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pipeline_tag: zero-shot-image-classification
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The model that corresponds to Q-Align (ICML2024).
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## Quick Start with AutoModel
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For this image,  start an AutoModel scorer with `transformers==4.36.1`:
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