Update cohere embedding models (#3704)

haystack/nodes/retriever/_embedding_encoder.py

@@ -477,7 +477,14 @@ def __init__(self, retriever: "EmbeddingRetriever"):
         self.api_key = retriever.api_key
         self.batch_size = min(16, retriever.batch_size)
         self.progress_bar = retriever.progress_bar
-        self.model: str = next((m for m in ["small", "medium", "large"] if m in retriever.embedding_model), "large")
+        self.model: str = next(
+            (
+                m
+                for m in ["small", "medium", "large", "multilingual-22-12", "finance-sentiment"]
+                if m in retriever.embedding_model
+            ),
+            "multilingual-22-12",
+        )
         self.tokenizer = AutoTokenizer.from_pretrained("gpt2")
 
     def _ensure_text_limit(self, text: str) -> str:

haystack/nodes/retriever/dense.py

@@ -1819,7 +1819,7 @@ def _preprocess_documents(self, docs: List[Document]) -> List[Document]:
     def _infer_model_format(model_name_or_path: str, use_auth_token: Optional[Union[str, bool]]) -> str:
         if any(m in model_name_or_path for m in ["ada", "babbage", "davinci", "curie"]):
             return "openai"
-        if model_name_or_path in ["small", "medium", "large"]:
+        if model_name_or_path in ["small", "medium", "large", "multilingual-22-12", "finance-sentiment"]:
             return "cohere"
         # Check if model name is a local directory with sentence transformers config file in it
         if Path(model_name_or_path).exists():