Update model config and README

README.md

@@ -1,5 +1,6 @@
 ---
 tags:
+- image-feature-extraction
 - timm
 - transformers
 pipeline_tag: image-feature-extraction
@@ -19,7 +20,7 @@ A DINOv3 ViT model image feature encoder. Distilled on LVD-1689M from the DINOv3
 * The original models keep RoPE periods as a persistent `bfloat16` buffer. `timm` generates `float32` periods at init. This results in some numerical differences, however the `timm` approach should be less problematic running on devices without bfloat16 support, and appears to work as well if not slightly better for fine-tuning. `model.rope.periods = model.rope.periods.to(torch.bfloat16).to(torch.float32)` will truncate the periods to bfloat16 and result in matching outputs.
 
 ## Model Details
-- **Model Type:** Image feature encoder
+- **Model Type:** Image Feature Encoder
 - **Model Stats:**
   - Params (M): 840.5
   - GMACs: 224.9
@@ -190,4 +191,4 @@ See the associated paper for details on the evaluation protocols
   doi = {10.5281/zenodo.4414861},
   howpublished = {\url{https://github.com/huggingface/pytorch-image-models}}
 }
-```
+```

config.json

@@ -4,7 +4,7 @@
   "num_features": 1280,
   "global_pool": "avg",
   "pretrained_cfg": {
-    "tag": "lvdm_1689m",
+    "tag": "lvd_1689m",
     "custom_load": false,
     "input_size": [
       3,