Zero Shot Transfer Image Classification On 8
Métriques
Accuracy (Private)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy (Private) | Paper Title | Repository |
|---|---|---|---|
| CoCa | 77.6 | CoCa: Contrastive Captioners are Image-Text Foundation Models | |
| EVA-CLIP-18B | 74.7 | EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters | - |
| InternVL-C | 73.9 | InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks | |
| BASIC | 76.1 | Combined Scaling for Zero-shot Transfer Learning | - |
| AltCLIP | 58.7 | AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities | |
| BASIC (Lion) | 77.2 | - | - |
| EVA-CLIP-E/14+ | 71.6 | EVA-CLIP: Improved Training Techniques for CLIP at Scale |
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