Update README.md

README.md

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-Experimental ONNX conversion of kaloscope model.  
-~~These need a re-export because i didnt specify dynamic axes during export which probably locked the model behind batch size = 1; otherwise they seem to work perfectly fine~~  
-25th oct: replaced existing onnx files with new exports that use dynamo=False and `dynamic_axes={"input": {0: "batch_size"}, "output": {0: "batch_size"},}` - scores seems to be same as original pytorch model and dynamo=True export  
+ONNX conversion of kaloscope model.  
 
 [🤗 Space Demo](https://huggingface.co/spaces/DraconicDragon/Kaloscope-artist-style-classifier) for ONNX & PyTorch inference implementation (incl. timm+lsnet; OpenVINO accelerate CPU inference; no Triton required - refer to [ska.py](https://huggingface.co/spaces/DraconicDragon/Kaloscope-artist-style-classifier/blob/main/lsnet/ska.py) or [here](https://github.com/spawner1145/comfyui-lsnet/pull/2))  
 Barebones standalone ONNX inference script (no timm or lsnet; scores are a tiny bit different - probably different img preprocessing): [onnx_barebones_inference.py](https://huggingface.co/DraconicDragon/Kaloscope-onnx-ema/blob/main/onnx_barebones_inference.py)
 
 - `kaloscope_1-0.onnx`: Exported from `best_checkpoint.pth` original Kaloscope release | dynamo=False, dynamic_axes={"input": {0: "batch_size"}, "output": {0: "batch_size"},}, opset_version=None (torch 2.8.0 used here defaults to 18 when None), optimization/constant folding enabled
 - `kaloscope_1-1.onnx`: Exported from `224-85.65/best_checkpoint.pth` aka v1.1 | Same settings as v1.0
+- `v2.0/kaloscope_2-0.onnx`: Exported from `Kaloscope2.0/448-90.13/best_checkpoint.pth` aka v2.0 | Same settings as v1.0
 
 Conversion/Export script: [colab notebook](https://huggingface.co/DraconicDragon/Kaloscope-onnx/blob/main/convert_scripts/kaloscope_pth2onnx_colab.ipynb)  
 theres an extra pytorch ema only version (`best_checkpoint_ema.pth`) of the model which is roughly 4 times smaller but seems to output different results; did not do extensive tests. ONNX version recommended over this (script used: [save_ema.py](https://huggingface.co/DraconicDragon/Kaloscope-onnx-ema/blob/main/save_ema.py))