Huggingface yaml tags and edits

README.md

@@ -2,9 +2,9 @@
 language: multilingual 
 ---
 
-## Model card: multilingual-clip
+## Multilingual-clip: XLM-Roberta-Large-Vit-B-32
 
-Multilingual-CLIP extends OpenAI's English text encoders to multiple other languages. This model *only* contains the multilingual text encoder. The corresponding image model `ViT-B-32` needs to be retrieved via instructions found on from OpenAI's [CLIP repository on Github](https://github.com/openai/CLIP). We provide a usage example below. 
+Multilingual-CLIP extends OpenAI's English text encoders to multiple other languages. This model *only* contains the multilingual text encoder. The corresponding image model `ViT-B-32` can be retrieved via instructions found on OpenAI's [CLIP repository on Github](https://github.com/openai/CLIP). We provide a usage example below. 
 
 ## Requirements
 
@@ -68,6 +68,7 @@ None of the M-CLIP models have been extensivly evaluated, but testing them on Tx
 | ----------------------------------|:-----: |:-----: |:-----: |:-----: | :-----: |:-----: |:-----: |:-----: |:-----: |:-----: |:-----: |
 | [OpenAI CLIP Vit-B/32](https://github.com/openai/CLIP)| 90.3 | - | - | - | - | - | - | - | - | - | - |
 | [OpenAI CLIP Vit-L/14](https://github.com/openai/CLIP)| 91.8 | - | - | - | - | - | - | - | - | - | - |
+| [OpenCLIP ViT-B-16+-](https://github.com/openai/CLIP)| 94.3 | - | - | - | - | - | - | - | - | - | - |
 | [LABSE Vit-L/14](https://huggingface.co/M-CLIP/LABSE-Vit-L-14)| 91.6 | 89.6 | 89.5 | 89.9 | 88.9 | 90.1 | 89.8 | 80.8 | 85.5 | 89.8 | 73.9 |
 | [XLM-R Large Vit-B/32](https://huggingface.co/M-CLIP/XLM-Roberta-Large-Vit-B-32)| 91.8 | 88.7 | 89.1 | 89.4 | 89.3 | 89.8| 91.4 | 82.1 | 86.1 | 88.8 | 81.0 |
 | [XLM-R Vit-L/14](https://huggingface.co/M-CLIP/XLM-Roberta-Large-Vit-L-14)| 92.4 | 90.6 | 91.0 | 90.0 | 89.7 | 91.1 | 91.3 | 85.2 | 85.8 | 90.3 | 81.9 |
@@ -76,4 +77,4 @@ None of the M-CLIP models have been extensivly evaluated, but testing them on Tx
 
 ## Training/Model details
 
-Details about the model training and data can be found in the [model card](https://github.com/FreddeFrallan/Multilingual-CLIP/blob/main/larger_mclip.md).
+Further details about the model training and data can be found in the [model card](https://github.com/FreddeFrallan/Multilingual-CLIP/blob/main/larger_mclip.md).