add embedding model by default to distribution templates (#617)

# What does this PR do?
Adds the sentence transformer provider and the `all-MiniLM-L6-v2`
embedding model to the default models to register in the run.yaml for
all providers.

## Test Plan
llama stack build --template together --image-type conda
llama stack run
~/.llama/distributions/llamastack-together/together-run.yaml

llama_stack/templates/meta-reference-quantized-gpu/meta_reference.py

@@ -6,10 +6,15 @@
 
 from pathlib import Path
 
+from llama_stack.apis.models.models import ModelType
+
 from llama_stack.distribution.datatypes import ModelInput, Provider
 from llama_stack.providers.inline.inference.meta_reference import (
     MetaReferenceQuantizedInferenceConfig,
 )
+from llama_stack.providers.inline.inference.sentence_transformers import (
+    SentenceTransformersInferenceConfig,
+)
 from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -34,6 +39,11 @@ def get_distribution_template() -> DistributionTemplate:
             checkpoint_dir="${env.INFERENCE_CHECKPOINT_DIR:null}",
         ),
     )
+    embedding_provider = Provider(
+        provider_id="sentence-transformers",
+        provider_type="inline::sentence-transformers",
+        config=SentenceTransformersInferenceConfig.sample_run_config(),
+    )
     memory_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
@@ -44,6 +54,14 @@ def get_distribution_template() -> DistributionTemplate:
         model_id="${env.INFERENCE_MODEL}",
         provider_id="meta-reference-inference",
     )
+    embedding_model = ModelInput(
+        model_id="all-MiniLM-L6-v2",
+        provider_id="sentence-transformers",
+        model_type=ModelType.embedding,
+        metadata={
+            "embedding_dimension": 384,
+        },
+    )
     return DistributionTemplate(
         name=name,
         distro_type="self_hosted",
@@ -54,10 +72,10 @@ def get_distribution_template() -> DistributionTemplate:
         run_configs={
             "run.yaml": RunConfigSettings(
                 provider_overrides={
-                    "inference": [inference_provider],
+                    "inference": [inference_provider, embedding_provider],
                     "memory": [memory_provider],
                 },
-                default_models=[inference_model],
+                default_models=[inference_model, embedding_model],
             ),
         },
         run_config_env_vars={