Update app.py

app.py

@@ -17,7 +17,7 @@ description = """
 
 It uses [Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base) model for image-to-text caption generation task.
 
-For Instagrammable captions, `mistralai/Mistral-7B-Instruct-v0.2` performs best, but try different models to see how they react to the same prompt.
+For Instagrammable captions, `mistralai/Mistral-7B-Instruct-v0.1` performs best, but try different models to see how they react to the same prompt.
 
 Built by [Bilge Yucel](https://twitter.com/bilgeycl) using [Haystack 2.0](https://github.com/deepset-ai/haystack) 💙
 """
@@ -54,8 +54,8 @@ with gr.Blocks(theme="soft") as demo:
         image = gr.Image(type="filepath")
         with gr.Column():
             model_name = gr.Dropdown(
-                ["mistralai/Mistral-7B-Instruct-v0.2","OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", "tiiuae/falcon-7b-instruct", "tiiuae/falcon-7b", "HuggingFaceH4/starchat-beta", "bigscience/bloom", "google/flan-t5-xxl"], 
-                value="mistralai/Mistral-7B-Instruct-v0.2", 
+                ["mistralai/Mistral-7B-Instruct-v0.1","OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", "tiiuae/falcon-7b-instruct", "tiiuae/falcon-7b", "HuggingFaceH4/starchat-beta", "bigscience/bloom", "google/flan-t5-xxl"], 
+                value="mistralai/Mistral-7B-Instruct-v0.1", 
                 label="Choose your model!"
                 )
             gr.Examples(["./whale.png", "./rainbow.jpeg", "./selfie.png"], inputs=image, label="Click on any example")