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- model_cards/ovl_classifier.md +3 -2
README.md
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If you use any of these models, please cite:
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```
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@misc{france2025ovlclassifiers,
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title = {Scentience-
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author = {Kordel Kade France},
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year = {2025},
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howpublished = {Hugging Face},
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If you use any of these models, please cite:
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```
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@misc{france2025ovlclassifiers,
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title = {Scentience-OVLC-v1: Joint Olfaction-Vision-Language Classifiers},
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author = {Kordel Kade France},
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year = {2025},
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howpublished = {Hugging Face},
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model_cards/ovl_classifier.md
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# Model Card: Scentience-
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## Model Details
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- **Fusion strategy:** Joint embedding space via multimodal contrastive training
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- **Parameter Count (Base):** 29.9M (without CLIP), 181.2M (with CLIP)
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- **Parameter Count (GAT):** 143.2M (without CLIP), 294.5M (with CLIP)
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- **Embedding Dimension:**
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- **License:** MIT
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- **Contact:** kordel@scentience.ai, kordel.france@utdallas.edu
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# Model Card: Scentience-OVLEC-v1
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## Model Details
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- **Fusion strategy:** Joint embedding space via multimodal contrastive training
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- **Parameter Count (Base):** 29.9M (without CLIP), 181.2M (with CLIP)
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- **Parameter Count (GAT):** 143.2M (without CLIP), 294.5M (with CLIP)
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- **Embedding Dimension:** 512
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- **Output Dimension:** 1 (single probability/logit)
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- **License:** MIT
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- **Contact:** kordel@scentience.ai, kordel.france@utdallas.edu
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