Zero Shot Transfer Image Classification On 6
Métriques
Accuracy (Private)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy (Private) |
|---|---|
| internvl-scaling-up-vision-foundation-models | 80.6 |
| lit-zero-shot-transfer-with-locked-image-text | 81.1 |
| pali-a-jointly-scaled-multilingual-language | 42.62 |
| eva-clip-improved-training-techniques-for | 79.6 |
| scaling-vision-transformers-to-22-billion | 87.6 |
| eva-clip-18b-scaling-clip-to-18-billion | 82.2 |
| learning-transferable-visual-models-from | 72.3 |
| pali-a-jointly-scaled-multilingual-language | 84.9 |
| coca-contrastive-captioners-are-image-text | 82.7 |