Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`google/vit-base-patch16-224-in21k`](https://huggingface.co/google/vit-base-patch16-224-in21k) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.

How did we find this information? We performed a regular expression match on your `README.md` file to determine the connection.

**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.

For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).

This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien).

If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co/librarian-bot) [Metadata Request Service](https://huggingface.co/spaces/librarian-bots/metadata_request_service)!

README.md

@@ -8,16 +8,17 @@ datasets:
 metrics:
 - accuracy
 widget:
-  - src: https://huggingface.co/RaymundoSGlz/vit_model_beans/resolve/main/bean_rust.jpeg
-    example_title: Bean rust
-  - src: https://huggingface.co/RaymundoSGlz/vit_model_beans/resolve/main/healthy.jpeg
-    example_title: Healthy
+- src: https://huggingface.co/RaymundoSGlz/vit_model_beans/resolve/main/bean_rust.jpeg
+  example_title: Bean rust
+- src: https://huggingface.co/RaymundoSGlz/vit_model_beans/resolve/main/healthy.jpeg
+  example_title: Healthy
+base_model: google/vit-base-patch16-224-in21k
 model-index:
 - name: vit_model_beans
   results:
   - task:
-      name: Image Classification
       type: image-classification
+      name: Image Classification
     dataset:
       name: beans
       type: beans
@@ -25,9 +26,9 @@ model-index:
       split: validation
       args: default
     metrics:
-    - name: Accuracy
-      type: accuracy
+    - type: accuracy
       value: 0.9924812030075187
+      name: Accuracy
 ---
 
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