Updates Eland install command in the vector search example (#2599) (#2600)

Co-authored-by: David Kyle <[email protected]>
(cherry picked from commit 3f38801)

Co-authored-by: István Zoltán Szabó <[email protected]>

Author: mergify[bot]

docs/en/stack/ml/nlp/ml-nlp-shared.asciidoc

@@ -1,16 +1,13 @@
 tag::nlp-eland-clone-docker-build[]
-You can use the {eland-docs}[Eland client] to install the {nlp} model. Eland 
-commands can be run in Docker. First, you need to clone the Eland repository 
-then create a Docker image of Eland:
+You can use the {eland-docs}[Eland client] to install the {nlp} model. Use the prebuilt  
+Docker image to run the Eland install model commands. Pull the latest image with:
 
 [source,shell]
 --------------------------------------------------
-git clone [email protected]:elastic/eland.git
-cd eland
-docker build -t elastic/eland .
+docker pull docker.elastic.co/eland/eland
 --------------------------------------------------
 
-After the script finishes, your Eland Docker client is ready to use.
+After the pull completes, your Eland Docker client is ready to use.
 end::nlp-eland-clone-docker-build[]
 
 tag::nlp-requirements[]

docs/en/stack/ml/nlp/ml-nlp-text-emb-vector-search-example.asciidoc

@@ -19,6 +19,11 @@ consists of real questions from the Microsoft Bing search engine and human
 generated answers for them. The example works with a sample of this data set, 
 uses a model to produce text embeddings, and then runs vector search on it.
 
+You can find 
+https://github.com/elastic/elasticsearch-labs/blob/main/notebooks/integrations/hugging-face/loading-model-from-hugging-face.ipynb[this example as a Jupyter notebook] 
+using the Python client in the `elasticsearch-labs` repo.
+
+
 [discrete]
 [[ex-te-vs-requirements]]
 == Requirements