Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`intfloat/multilingual-e5-large`](https://huggingface.co/intfloat/multilingual-e5-large) 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). Your input is invaluable to us!

README.md

@@ -1,31 +1,32 @@
 ---
-datasets:
-- xnli
-model-index:
-- name: multilingual-e5-large-xnli
-  results: []
-pipeline_tag: zero-shot-classification
 language:
 - multilingual
-- en 
-- ar 
-- bg 
-- de 
-- el 
-- es 
+- en
+- ar
+- bg
+- de
+- el
+- es
 - fr
 - hi
-- ru 
-- sw 
-- th 
-- tr 
-- ur 
-- vi 
+- ru
+- sw
+- th
+- tr
+- ur
+- vi
 - zh
 license: mit
+datasets:
+- xnli
+pipeline_tag: zero-shot-classification
 widget:
-- text: "Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU"
-  candidate_labels: "politics, economy, entertainment, environment"
+- text: Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU
+  candidate_labels: politics, economy, entertainment, environment
+base_model: intfloat/multilingual-e5-large
+model-index:
+- name: multilingual-e5-large-xnli
+  results: []
 ---
 
 # multilingual-e5-large-xnli