Update README.md

README.md

@@ -30,14 +30,14 @@ The model supports multi-image and multi-prompt generation. Meaning that you can
 
 ### Using `pipeline`:
 
-Below we used [`"llava-hf/bakLlava-v1-hf"`](https://huggingface.co/llava-hf/bakLlava-v1-hf) checkpoint.
+Below we used [`"llava-hf/llava-1.5-13b-hf"`](https://huggingface.co/llava-hf/llava-1.5-13b-hf) checkpoint.
 
 ```python
 from transformers import pipeline
 from PIL import Image    
 import request
 
-model_id = "llava-hf/bakLlava-v1-hf"
+model_id = "llava-hf/llava-1.5-13b-hf"
 pipe = pipeline("image-to-text", model=model_id)
 url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"
 
@@ -60,7 +60,7 @@ from PIL import Image
 import torch
 from transformers import AutoProcessor, LlavaForConditionalGeneration
 
-model_id = "llava-hf/llava-1.5-7b-hf"
+model_id = "llava-hf/llava-1.5-13b-hf"
 
 prompt = "<image> \nUSER: What are these?\nASSISTANT:"
 image_file = "http://images.cocodataset.org/val2017/000000039769.jpg"