Update README.md with new model card content

README.md

@@ -1,31 +1,51 @@
 ---
 library_name: keras-hub
 ---
-This is a [`DINOV3` model](https://keras.io/api/keras_hub/models/dinov3) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
-Model config:
-* **name:** dinov3_backbone
-* **trainable:** True
-* **dtype:** {'module': 'keras', 'class_name': 'DTypePolicy', 'config': {'name': 'float32'}, 'registered_name': None}
-* **patch_size:** 16
-* **num_layers:** 12
-* **hidden_dim:** 384
-* **num_heads:** 6
-* **intermediate_dim:** 1536
-* **num_register_tokens:** 4
-* **use_mask_token:** True
-* **layer_scale_init_value:** 1.0
-* **hidden_activation:** silu
-* **use_gated_mlp:** True
-* **use_query_bias:** True
-* **use_key_bias:** False
-* **use_value_bias:** True
-* **use_proj_bias:** True
-* **use_mlp_bias:** True
-* **attention_dropout:** 0.0
-* **drop_path_rate:** 0.0
-* **layer_norm_eps:** 1e-05
-* **image_shape:** [224, 224, 3]
-* **rope_theta:** 100.0
-* **apply_layernorm:** False
-
-This model card has been generated automatically and should be completed by the model author. See [Model Cards documentation](https://huggingface.co/docs/hub/model-cards) for more information.
+### Model Overview
+Vision Transformer (ViT) and ConvNeXt models trained using the DINOv3 method.
+
+**Reference**
+
+- [DINOv3: Learning Robust Visual Features without Supervision](https://arxiv.org/abs/2508.10104)
+
+DINOv3 offers a powerful, generalist visual backbone learned entirely from
+unlabeled images as described in DINOv3: Learning Robust Visual Features
+without Supervision.
+
+## Links
+
+* [DINOv3 Quickstart Notebook] - coming soon
+* [DINOv3 API Documentation] - coming soon
+* [DINOv3 Beginner Guide] - coming soon
+* [KerasHub Model Publishing Guide](https://keras.io/guides/keras_hub/upload/)
+
+
+## Installation
+
+Keras and KerasHub can be installed with:
+
+```
+pip install -U -q keras-hub
+pip install -U -q keras
+```
+
+Jax, TensorFlow, and Torch come preinstalled in Kaggle Notebooks. For instructions on installing them in another environment see the [Keras Getting Started](https://keras.io/getting_started/) page.
+
+## Presets
+
+The following model checkpoints are provided by the Keras team. Weights have been ported from: https://huggingface.co. Full code examples for each are available below.
+
+| Preset name | Parameters | Description |
+|---|---|---|
+| dinov3_vit_small_lvd1689m | 21.6M | Vision Transformer (small-sized model) trained on LVD-1689M using DINOv3. |
+| dinov3_vit_small_plus_lvd1689m | 29M | Vision Transformer (small-plus-sized model) trained on LVD-1689M using DINOv3. |
+| dinov3_vit_base_lvd1689m | 86M | Vision Transformer (base-sized model) trained on LVD-1689M using DINOv3. |
+| dinov3_vit_large_lvd1689m | 300M | Vision Transformer (large-sized model) trained on LVD-1689M using DINOv3. |
+| dinov3_vit_huge_plus_lvd1689m | 840M | Vision Transformer (huge-plus-sized model) trained on LVD-1689M using DINOv3. |
+| dinov3_vit_7b_lvd1689m | 6.7B | Vision Transformer (7B-sized model) trained on LVD-1689M using DINOv3. |
+| dinov3_vit_large_sat493m | 300M | Vision Transformer (large-sized model) trained on SAT-493M using DINOv3. |
+| dinov3_vit_7b_sat493m | 6.7B | Vision Transformer (7B-sized model) trained on SAT-493M using DINOv3. |
+
+
+All the models weights are under DINO V3 license: https://ai.meta.com/resources/models-and-libraries/dinov3-license/
+