Update README.md

README.md

@@ -9,29 +9,29 @@ library_name: transformers
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 <br>
 
-# LoViM Model Card
+# BLIVA Model Card
 
 ## Model details
 
 **Model type:**
-LoViM is an open-source Vision-Languagde model trained by initializing from InstructBLIP and alignment with Vicuna on multimodal instruction-finetuning data.
+BLIVA is an open-source Vision-Languagde model trained by initializing from InstructBLIP and alignment with Vicuna on multimodal instruction-finetuning data.
 It composes of an EVA-CLIP vision encoder, a Q-Former, a projection layer and an auto-regressive language model, based on the decoder only transformer architecture.
 
 **Model date:**
-LoViM_FlanT5 was trained in July 2023.
+BLIVA_FlanT5 was trained in July 2023.
 
 **Paper or resources for more information:**
-https://gordonhu608.github.io/lovim/
+https://gordonhu608.github.io/BLIVA/
 
 **License:**
 BSD 3-Clause License
 
 **Where to send questions or comments about the model:**
-https://github.com/mlpc-ucsd/LoViM
+https://github.com/mlpc-ucsd/BLIVA
 
 ## Intended use
 **Primary intended uses:**
-The primary use of LoViM FlanT5 is for commercial use on large multimodal models. 
+The primary use of BLIVA FlanT5 is for commercial use on large multimodal models. 
 
 **Primary intended users:**
 The primary intended users of this model is for commercial companies in computer vision, natural language processing, machine learning, and artificial intelligence.
@@ -46,4 +46,4 @@ For zero-shot evaluation on general image task, we selected Nocaps, Flickr30K, V
 
 For zero-shot evaluation on text-rich image OCR task, we selected ST-VQA, OCR-VQA, Text-VQA, and Doc-VQA.
 
-More detials are in our github, https://github.com/mlpc-ucsd/LoViM
+More detials are in our github, https://github.com/mlpc-ucsd/BLIVA