Update README.md

README.md

@@ -117,7 +117,7 @@ base_model:
 - lmms-lab/llava-onevision-qwen2-7b-si
 ---
 
-# LLaVA-Video-7B-Qwen2
+# LLaVA-NeXT-Video-7B-Qwen2
 
 ##  Table of Contents
 
@@ -130,7 +130,7 @@ base_model:
 
 ## Model Summary
 
-The LLaVA-Video models are 7/72B parameter models trained on [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Video-SFT-Data), based on Qwen2 language model with a context window of 32K tokens.
+The LLaVA-NeXT-Video models are 7/72B parameter models trained on [LLaVA-NeXT-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Video-SFT-Data), based on Qwen2 language model with a context window of 32K tokens.
 
 - **Repository:** [LLaVA-VL/LLaVA-NeXT](https://github.com/LLaVA-VL/LLaVA-NeXT?tab=readme-ov-file)
 - **Point of Contact:** [Yuanhan Zhang](https://zhangyuanhan-ai.github.io/)
@@ -141,7 +141,7 @@ The LLaVA-Video models are 7/72B parameter models trained on [LLaVA-Video-178K](
 
 ### Intended use
 
-The model was trained on [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Video-SFT-Data) and have the ability to interact with images, multi-image and videos, but specific to videos.
+The model was trained on [LLaVA-NeXT-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Video-SFT-Data) and have the ability to interact with images, multi-image and videos, but specific to videos.
 
 **Feel free to share your generations in the Community tab!**
 
@@ -182,7 +182,7 @@ def load_video(self, video_path, max_frames_num,fps=1,force_sample=False):
     spare_frames = vr.get_batch(frame_idx).asnumpy()
     # import pdb;pdb.set_trace()
     return spare_frames,frame_time,video_time
-pretrained = "lmms-lab/LLaVA-Video-7B-Qwen2"
+pretrained = "lmms-lab/LLaVA-NeXT-Video-7B-Qwen2"
 model_name = "llava_qwen"
 device = "cuda"
 device_map = "auto"