Update app.py

app.py

@@ -17,17 +17,10 @@ import subprocess
 subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
 
 models = {
-    'microsoft/Florence-2-large-ft': AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-large-ft', trust_remote_code=True).to("cuda").eval(),
-    'microsoft/Florence-2-large': AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-large', trust_remote_code=True).to("cuda").eval(),
-    'microsoft/Florence-2-base-ft': AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-base-ft', trust_remote_code=True).to("cuda").eval(),
-    'microsoft/Florence-2-base': AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True).to("cuda").eval(),
-}
+    'microsoft/Florence-2-large': AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-large', trust_remote_code=True).to("cuda").eval()}
 
 processors = {
-    'microsoft/Florence-2-large-ft': AutoProcessor.from_pretrained('microsoft/Florence-2-large-ft', trust_remote_code=True),
-    'microsoft/Florence-2-large': AutoProcessor.from_pretrained('microsoft/Florence-2-large', trust_remote_code=True),
-    'microsoft/Florence-2-base-ft': AutoProcessor.from_pretrained('microsoft/Florence-2-base-ft', trust_remote_code=True),
-    'microsoft/Florence-2-base': AutoProcessor.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True),
+    'microsoft/Florence-2-large': AutoProcessor.from_pretrained('microsoft/Florence-2-large', trust_remote_code=True)
 }
 
 
@@ -210,12 +203,9 @@ with gr.Blocks(css=css) as demo:
                 input_img = gr.Image(label="Input Picture")
                 model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value='microsoft/Florence-2-large')
                 task_prompt = gr.Dropdown(choices=[
-                    'Caption', 'Detailed Caption', 'More Detailed Caption', 'Object Detection',
-                    'Dense Region Caption', 'Region Proposal', 'Caption to Phrase Grounding',
-                    'Referring Expression Segmentation', 'Region to Segmentation',
-                    'Open Vocabulary Detection', 'Region to Category', 'Region to Description',
+                    'Caption', 'Detailed Caption', 'More Detailed Caption',
                     'OCR', 'OCR with Region'
-                ], label="Task Prompt", value= 'Caption')
+                ], label="Task Prompt", value= 'More Detailed Caption')
                 text_input = gr.Textbox(label="Text Input (optional)")
                 submit_btn = gr.Button(value="Submit")
             with gr.Column():