diff --git a/demos/continuous_batching/accuracy/README.md b/demos/continuous_batching/accuracy/README.md
index db76509fc6..c7acb1b678 100644
--- a/demos/continuous_batching/accuracy/README.md
+++ b/demos/continuous_batching/accuracy/README.md
@@ -9,7 +9,7 @@ It reports end to end quality of served model from the client application point
 
 Install the framework via pip:
 ```console
-pip3 install --extra-index-url "https://download.pytorch.org/whl/cpu" lm_eval[api] langdetect immutabledict dotenv openai
+pip3 install --extra-index-url "https://download.pytorch.org/whl/cpu" lm_eval[api] langdetect immutabledict dotenv openai hf_transfer
 ```
 
 ## Exporting the models
diff --git a/demos/embeddings/README.md b/demos/embeddings/README.md
index b74042f754..cc7c689389 100644
--- a/demos/embeddings/README.md
+++ b/demos/embeddings/README.md
@@ -489,7 +489,7 @@ Difference score with HF AutoModel: 0.020293646680283224
 
 It is easy also to run model evaluation using [MTEB](https://github.com/embeddings-benchmark/mteb) framework using a custom class based on openai model:
 ```bash
-pip install "mteb<2" einops openai --extra-index-url "https://download.pytorch.org/whl/cpu"
+pip install "mteb==1.39.7" "einops==0.8.1" "openai==2.7.2" "pillow==12.0.0" "transformers==4.57.6" --extra-index-url "https://download.pytorch.org/whl/cpu"
 curl https://raw.githubusercontent.com/openvinotoolkit/model_server/refs/heads/main/demos/embeddings/ovms_mteb.py -o ovms_mteb.py
 python ovms_mteb.py --model BAAI/bge-large-en-v1.5 --service_url http://localhost:8000/v3/embeddings
 ```