Update README.md

README.md

@@ -1,35 +1,35 @@
----
-title: WD EVA02 LoRA ONNX Tagger
-emoji: 🖼️
-colorFrom: blue
-colorTo: green
-sdk: gradio
-sdk_version: 4.433.0 # Updated Gradio SDK version
-app_file: app.py
-license: apache-2.0 # Or your preferred license
-# Hardware Selection:
-# For CPU execution (recommended if GPU isn't strictly needed):
-# hardware: cpu-upgrade 
-# For GPU execution (requires compatible CUDA setup):
-# hardware: cuda-t4-small 
-# pinned: false # Set to true if you want to pin the hardware
-# hf_token: YOUR_HF_TOKEN # Use secrets instead!
----
-
-# WD EVA02 LoRA ONNX Tagger
-
-This Space demonstrates image tagging using a fine-tuned WD EVA02 model (converted to ONNX format).
-
-Model Repository: [celstk/wd-eva02-lora-onnx](https://huggingface.co/celstk/wd-eva02-lora-onnx)
-
-**How to Use:**
-1. Upload an image using the upload button.
-2. Alternatively, paste an image URL into the browser (experimental paste handling).
-3. Adjust the tag thresholds if needed.
-4. Choose the output mode (Tags only or include visualization).
-5. Click the "Predict" button.
-
-**Note:**
-- This Space uses a model from a **private** repository (`celstk/wd-eva02-lora-onnx`). You might need to duplicate this space and add your Hugging Face token (`HF_TOKEN`) to the Space secrets to allow downloading the model files.
-- Image pasting behavior might vary across browsers.
+---
+title: WD EVA02 LoRA ONNX Tagger
+emoji: 🖼️
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 4.43.0 # Updated Gradio SDK version
+app_file: app.py
+license: apache-2.0 # Or your preferred license
+# Hardware Selection:
+# For CPU execution (recommended if GPU isn't strictly needed):
+# hardware: cpu-upgrade 
+# For GPU execution (requires compatible CUDA setup):
+# hardware: cuda-t4-small 
+pinned: false # Set to true if you want to pin the hardware
+# hf_token: YOUR_HF_TOKEN # Use secrets instead!
+---
+
+# WD EVA02 LoRA ONNX Tagger
+
+This Space demonstrates image tagging using a fine-tuned WD EVA02 model (converted to ONNX format).
+
+Model Repository: [celstk/wd-eva02-lora-onnx](https://huggingface.co/celstk/wd-eva02-lora-onnx)
+
+**How to Use:**
+1. Upload an image using the upload button.
+2. Alternatively, paste an image URL into the browser (experimental paste handling).
+3. Adjust the tag thresholds if needed.
+4. Choose the output mode (Tags only or include visualization).
+5. Click the "Predict" button.
+
+**Note:**
+- This Space uses a model from a **private** repository (`celstk/wd-eva02-lora-onnx`). You might need to duplicate this space and add your Hugging Face token (`HF_TOKEN`) to the Space secrets to allow downloading the model files.
+- Image pasting behavior might vary across browsers.
 - If you require GPU acceleration, uncomment the `hardware: cuda-t4-small` line above and ensure the environment has the necessary CUDA libraries compatible with `onnxruntime-gpu`. The current setup defaults to CPU due to potential CUDA library mismatches in the standard Spaces environment.