Update README.md

README.md

@@ -37,14 +37,14 @@ The model supports multi-image and multi-prompt generation. Meaning that you can
 
 ### Using `pipeline`:
 
-Below we used [`"snorfyang/llava-1.5-7b-lora-hf"`](https://huggingface.co/snorfyang/llava-1.5-7b-lora-hf) checkpoint.
+Below we used [`"snorfyang/llava-v1.5-7b-lora-hf"`](https://huggingface.co/snorfyang/llava-v1.5-7b-lora-hf) checkpoint.
 
 ```python
 from transformers import pipeline
 from PIL import Image    
 import requests
 
-model_id = "snorfyang/llava-1.5-7b-lora-hf"
+model_id = "snorfyang/llava-v1.5-7b-lora-hf"
 pipe = pipeline("image-to-text", model=model_id)
 url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"
 
@@ -67,7 +67,7 @@ from PIL import Image
 import torch
 from transformers import AutoProcessor, LlavaForConditionalGeneration
 
-model_id = "snorfyang/llava-1.5-7b-lora-hf"
+model_id = "snorfyang/llava-v1.5-7b-lora-hf"
 
 prompt = "USER: <image>\nWhat are these?\nASSISTANT:"
 image_file = "http://images.cocodataset.org/val2017/000000039769.jpg"