fix readme.md

README.md

@@ -25,7 +25,8 @@ tags:
 
 Paper: [Per-Pixel Classification is Not All You Need for Semantic Segmentation (arXiv:2107.06278)](https://arxiv.org/abs/2107.06278) · [HF Papers](https://huggingface.co/papers/2107.06278)
 
-MaskFormer reframes segmentation as mask classification: a backbone and pixel decoder feed a transformer decoder whose queries each predict a binary mask and a class. One architecture covers semantic, instance, and panoptic outputs via post-processing.\n
+MaskFormer reframes segmentation as mask classification: a backbone and pixel decoder feed a transformer decoder whose queries each predict a binary mask and a class. One architecture covers semantic, instance, and panoptic outputs via post-processing.
+
 For more details on the model, please go to the upstream [model card](https://huggingface.co/facebook/maskformer-swin-tiny-coco).
 
 Pure-**Keras 3** conversion of [`facebook/maskformer-swin-tiny-coco`](https://huggingface.co/facebook/maskformer-swin-tiny-coco) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
@@ -39,10 +40,10 @@ import os
 os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
 
 from PIL import Image
-from {meta['import_path']} import {meta['load_cls']}, {meta['proc_cls']}
+from kerasformers.models.maskformer import MaskFormerUniversalSegment, MaskFormerImageProcessor
 
-model = {meta["load_cls"]}.from_weights("kerasformers/{variant}")
-processor = {meta["proc_cls"]}.from_weights("kerasformers/{variant}")
+model = MaskFormerUniversalSegment.from_weights("kerasformers/maskformer-swin-tiny-coco")
+processor = MaskFormerImageProcessor.from_weights("kerasformers/maskformer-swin-tiny-coco")
 
 image = Image.open("your_image.jpg").convert("RGB")
 output = model(processor(image)["pixel_values"], training=False)