Merge README edits from HF

README.md

@@ -31,15 +31,15 @@ pipeline_tag: image-classification
 
 | Model | Params (M) | MACs (G) | Top-1 Acc (%) | Checkpoint (pth) |
 |:---|:---:|:---:|:---:|:---:|
-| GeoViG-Ti | 3.5 | 0.9 | 75.2 | [Download](https://huggingface.co/TODO/geovig/resolve/main/pth/geovig_ti.pth) |
-| GeoViG-S | 5.0 | 1.2 | 77.5 | [Download](https://huggingface.co/TODO/geovig/resolve/main/pth/geovig_s.pth) |
-| GeoViG-M | 10.3 | 2.2 | 80.7 | [Download](https://huggingface.co/TODO/geovig/resolve/main/pth/geovig_m.pth) |
-| GeoViG-B | 19.7 | 4.5 | 82.4 | [Download](https://huggingface.co/TODO/geovig/resolve/main/pth/geovig_b.pth) |
+| GeoViG-Ti | 3.5 | 0.9 | 75.2 | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/pth/geovig_ti_5e4_8G_300_75_22/checkpoint.pth) |
+| GeoViG-S | 5.0 | 1.2 | 77.5 | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/pth/geovig_s_5e4_8G_300_77_48/checkpoint.pth) |
+| GeoViG-M | 10.3 | 2.2 | 80.7 | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/pth/geovig_m_5e4_8G_300_80_70/checkpoint.pth) |
+| GeoViG-B | 19.7 | 4.5 | 82.4 | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/pth/geovig_b_5e4_8G_300_82_38/checkpoint.pth) |
 
 Trained for 300 epochs on 8× NVIDIA A100 GPUs, batch size 1024, AdamW optimizer (lr=5e-4, weight decay=0.05), cosine schedule with 5-epoch warmup. Augmentations: RandAugment, Mixup (p=0.8), CutMix (p=1.0).
 
-For CoreML checkpoint, please check: 
-For IPA chechpoints, please check:
+For CoreML checkpoint, please check: https://huggingface.co/OmarAlasqa/GeoViG/tree/main/CoreML
+For IPA chechpoints, please check: https://huggingface.co/OmarAlasqa/GeoViG/tree/main/IPA
 ---
 
 ### 📦 Object Detection & Instance Segmentation — MS COCO 2017
@@ -48,8 +48,8 @@ Backbone used with **Mask R-CNN**, 1× schedule (12 epochs), pretrained on Image
 
 | Backbone | Params (M) | Box AP | Box AP₅₀ | Box AP₇₅ | Mask AP | Mask AP₅₀ | Mask AP₇₅ | Checkpoint |
 |:---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
-| GeoViG-M | 10.3 | 40.7 | 62.4 | 44.1 | 37.7 | 59.6 | 40.5 | [Download](https://huggingface.co/TODO/geovig/resolve/main/detection/geovig_m_coco.pth) |
-| GeoViG-B | 19.7 | 42.5 | 64.0 | 46.8 | 38.9 | 61.2 | 41.7 | [Download](https://huggingface.co/TODO/geovig/resolve/main/detection/geovig_b_coco.pth) |
+| GeoViG-M | 10.3 | 40.7 | 62.4 | 44.1 | 37.7 | 59.6 | 40.5 | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/coco_det_seg_pth/geovig_m_det_seg/epoch_12.pth) |
+| GeoViG-B | 19.7 | 42.5 | 64.0 | 46.8 | 38.9 | 61.2 | 41.7 | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/coco_det_seg_pth/geovig_b_det_seg/epoch_12.pth) |
 
 ---
 
@@ -59,13 +59,13 @@ Backbone used with **Mask R-CNN**, 1× schedule (12 epochs), pretrained on Image
 
 | Model | Params (M) | mAP | Dice ↑ | IoU ↑ | Hausdorff Dist ↓ | Checkpoint |
 |:---|:---:|:---:|:---:|:---:|:---:|:---:|
-| GeoViG-M | 29.57 | 0.990 | **0.945** | **0.909** | **12.94** | [Download](https://huggingface.co/TODO/geovig/resolve/main/medical/geovig_m_kvasir.pth) |
+| GeoViG-M | 29.57 | 0.990 | **0.945** | **0.909** | **12.94** | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/medical/kvasir_geovig_m/checkpoint.pth) |
 
 **Data Science Bowl 2018 — Nuclei Segmentation**
 
 | Model | Params (M) | mAP | Dice ↑ | IoU ↑ | Hausdorff Dist ↓ | Checkpoint |
 |:---|:---:|:---:|:---:|:---:|:---:|:---:|
-| GeoViG-M | 29.57 | 0.859 | **0.908** | **0.839** | **5.19** | [Download](https://huggingface.co/TODO/geovig/resolve/main/medical/geovig_m_dsb2018.pth) |
+| GeoViG-M | 29.57 | 0.859 | **0.908** | **0.839** | **5.19** | [Download](https://huggingface.co/OmarAlasqa/GeoViG/blob/main/medical/dsb_geovig_m/checkpoint.pth) |
 
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