Upload 5 files

app.py

@@ -1,5 +1,5 @@
-import gradio as gr
 import spaces
+import gradio as gr
 
 from utils import (
     gradio_copy_text,
@@ -39,7 +39,7 @@ def description_ui2():
  [Lamini-Prompt-Enchance](https://huggingface.co/gokaygokay/Lamini-Prompt-Enchance),\
  [Lamini-Prompt-Enchance-Long](https://huggingface.co/gokaygokay/Lamini-Prompt-Enchance-Long),\
  [Flux-Prompt-Enhance](https://huggingface.co/gokaygokay/Flux-Prompt-Enhance),\
- MiaoshouAI's [Florence-2-base-PromptGen](https://huggingface.co/MiaoshouAI/Florence-2-base-PromptGen).
+ MiaoshouAI's [Florence-2-base-PromptGen-v1.5](https://huggingface.co/MiaoshouAI/Florence-2-base-PromptGen-v1.5).
 """
     )
 
@@ -55,7 +55,7 @@ def main():
                     input_tag_type = gr.Radio(label="Convert tags to", info="danbooru for Animagine, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru")
                     recom_prompt = gr.Radio(label="Insert reccomended prompt", choices=["None", "Animagine", "Pony"], value="None", interactive=True)
                     keep_tags = gr.Radio(label="Remove tags leaving only the following", choices=["body", "dress", "all"], value="all")
-                image_algorithms = gr.CheckboxGroup(["Use WD Tagger", "Use Florence-2-SD3-Long-Captioner", "Use Florence-2-base-PromptGen", "Use Florence-2-Flux","Use Florence-2-Flux-Large"], label="Algorithms", value=["Use WD Tagger", "Use Florence-2-SD3-Long-Captioner"])
+                image_algorithms = gr.CheckboxGroup(["Use WD Tagger", "Use Florence-2-SD3-Long-Captioner", "Use Florence-2-base-PromptGen", "Use Florence-2-Flux", "Use Florence-2-Flux-Large"], label="Algorithms", value=["Use WD Tagger", "Use Florence-2-Flux"])
                 generate_from_image_btn = gr.Button(value="GENERATE TAGS FROM IMAGE", size="lg", variant="primary")
             with gr.Group():
                 with gr.Row():

fl2basepromptgen.py

@@ -1,5 +1,5 @@
-from transformers import AutoProcessor, AutoModelForCausalLM
 import spaces
+from transformers import AutoProcessor, AutoModelForCausalLM
 from PIL import Image 
 import torch
 
@@ -9,8 +9,8 @@ subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENT
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 try:
-    fl_model = AutoModelForCausalLM.from_pretrained('MiaoshouAI/Florence-2-base-PromptGen', trust_remote_code=True).to("cpu").eval()
-    fl_processor = AutoProcessor.from_pretrained('MiaoshouAI/Florence-2-base-PromptGen', trust_remote_code=True)
+    fl_model = AutoModelForCausalLM.from_pretrained('MiaoshouAI/Florence-2-base-PromptGen-v1.5', trust_remote_code=True).to("cpu").eval()
+    fl_processor = AutoProcessor.from_pretrained('MiaoshouAI/Florence-2-base-PromptGen-v1.5', trust_remote_code=True)
 except Exception as e:
     print(e)
     fl_model = fl_processor = None

fl2flux.py

@@ -1,5 +1,5 @@
-from transformers import AutoProcessor, AutoModelForCausalLM
 import spaces
+from transformers import AutoProcessor, AutoModelForCausalLM
 import re
 from PIL import Image 
 import torch

fl2sd3longcap.py

@@ -1,5 +1,5 @@
-from transformers import AutoProcessor, AutoModelForCausalLM
 import spaces
+from transformers import AutoProcessor, AutoModelForCausalLM
 import re
 from PIL import Image 
 import torch