fix readme.md

README.md

@@ -24,7 +24,8 @@ tags:
 
 Paper: [Depth Anything V2 (arXiv:2406.09414)](https://arxiv.org/abs/2406.09414) · [HF Papers](https://huggingface.co/papers/2406.09414)
 
-Depth Anything V2 keeps V1's architecture and improves data (synthetic labels plus large-scale pseudo-labeling). Relative heads return unitless inverse depth; metric indoor/outdoor heads return metres.\n
+Depth Anything V2 keeps V1's architecture and improves data (synthetic labels plus large-scale pseudo-labeling). Relative heads return unitless inverse depth; metric indoor/outdoor heads return metres.
+
 For more details on the model, please go to the upstream [model card](https://huggingface.co/depth-anything/Depth-Anything-V2-Base-hf).
 
 Pure-**Keras 3** conversion of [`depth-anything/Depth-Anything-V2-Base-hf`](https://huggingface.co/depth-anything/Depth-Anything-V2-Base-hf) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
@@ -38,10 +39,10 @@ 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.depth_anything_v2 import DepthAnythingV2DepthEstimation, DepthAnythingV2ImageProcessor
 
-model = {meta["load_cls"]}.from_weights("kerasformers/{variant}")
-processor = {meta['proc_cls']}()
+model = DepthAnythingV2DepthEstimation.from_weights("kerasformers/depth_anything_v2_base")
+processor = DepthAnythingV2ImageProcessor()
 
 image = Image.open("your_image.jpg").convert("RGB")
 output = model(processor(image)["pixel_values"], training=False)