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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README.md
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| Q-Align (IQA+VQA) | **0.944**/0.949/**0.797** | 0.931/0.934/0.764 | **0.952**/**0.953**/**0.809** | **0.892**/**0.899**/**0.715** | 0.874/0.846/0.684 | 0.852/0.876/0.663 | 0.739/0.782/0.526 |
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| **OneAlign** (IQA+IAA+VQA) | 0.941/**0.950**/0.791 | **0.932**/**0.935**/**0.766** | 0.941/0.942/0.791 | 0.881/0.894/0.699 | **0.887**/**0.856**/**0.699** | **0.881**/**0.906**/**0.699** | **0.801**/**0.838**/**0.602** |
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## IAA Results (Spearman/Pearson
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| Dataset | AVA_test |
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| *VILA (CVPR, 2023)* | 0.774/0.774 |
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| Q-Align (IAA) | 0.822/0.817 |
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| **OneAlign** (IQA+IAA+VQA) | **0.823**/**0.819** |
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## VQA Results (Spearman/Pearson
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| Datasets | LSVQ_test | LSVQ_1080p | KoNViD-1k | MaxWell_test |
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| --- | --- | --- | --- | --- |
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| Q-Align (IQA+VQA) | **0.944**/0.949/**0.797** | 0.931/0.934/0.764 | **0.952**/**0.953**/**0.809** | **0.892**/**0.899**/**0.715** | 0.874/0.846/0.684 | 0.852/0.876/0.663 | 0.739/0.782/0.526 |
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| **OneAlign** (IQA+IAA+VQA) | 0.941/**0.950**/0.791 | **0.932**/**0.935**/**0.766** | 0.941/0.942/0.791 | 0.881/0.894/0.699 | **0.887**/**0.856**/**0.699** | **0.881**/**0.906**/**0.699** | **0.801**/**0.838**/**0.602** |
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## IAA Results (Spearman/Pearson)
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| Dataset | AVA_test |
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| --- | --- |
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| *VILA (CVPR, 2023)* | 0.774/0.774 |
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| Q-Align (IAA) | 0.822/0.817 |
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| **OneAlign** (IQA+IAA+VQA) | **0.823**/**0.819** |
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## VQA Results (Spearman/Pearson)
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| Datasets | LSVQ_test | LSVQ_1080p | KoNViD-1k | MaxWell_test |
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| --- | --- | --- | --- | --- |
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