nvidia
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MM-Embed

nada5 commited on Oct 30, 2024

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@@ -19,7 +19,7 @@ MMEmbed presents several new training strategies, including modality-aware hard
 ## How to use
-Here are two examples of how to encode queries and passages using Huggingface-transformer. Please find the required package version [here](https://huggingface.co/nvidia/MMEmbed#1-required-packages). See more instructions in various retrieval scenario [here](https://huggingface.co/nvidia/MMEmbed/blob/main/instructions.json)
 ### Usage of Multimodal Retrieval (HuggingFace Transformers)
 ```python

 ## How to use
+Here are two examples of how to encode queries and passages using Huggingface-transformer. Please find the required package version [here](https://huggingface.co/nvidia/MM-Embed#1-required-packages). See more instructions in various retrieval scenario [here](Here are two examples of how to encode queries and passages using Huggingface-transformer. Please find the required package version [here](https://huggingface.co/nvidia/MM-Embed#1-required-packages). See more instructions in various retrieval scenario [here](https://huggingface.co/nvidia/MM-Embed/blob/main/instructions.json)
 ### Usage of Multimodal Retrieval (HuggingFace Transformers)
 ```python