update

README.md

@@ -7,33 +7,18 @@ license: cc-by-nc-4.0
 ## Model details
 
 **Model type:**
-CuMo-7B is based on [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
+CuMo-mistral-7B is a multimodal LLM based on [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
 
 **Model date:**
-LLaVA-v1.6-Mistral-7B was trained in December 2023.
+CuMo-mistral-7B was trained in April 2024.
 
-**Paper or resources for more information:**
-https://llava-vl.github.io/
+**Github Page:**
+https://github.com/SHI-Labs/CuMo
 
 ## License
+[cumo-mistral-7b](https://github.com/SHI-Labs/CuMo) license
 [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) license.
 
-**Where to send questions or comments about the model:**
-https://github.com/haotian-liu/LLaVA/issues
 
 ## Intended use
-**Primary intended uses:**
-The primary use of LLaVA is research on large multimodal models and chatbots.
-
-**Primary intended users:**
-The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
-
-## Training dataset
-- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
-- 158K GPT-generated multimodal instruction-following data.
-- 500K academic-task-oriented VQA data mixture.
-- 50K GPT-4V data mixture.
-- 40K ShareGPT data.
-
-## Evaluation dataset
-A collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.
+The primary use of CuMo is research on large multimodal models and chatbots.