diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 7eb89881d647b068bebd5995351f11b9f47a2532..9dedc36a6754b1addc20b174207665758aff982e 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -1,4 +1,4 @@
-image: "clarinpl/python:3.8"
+image: "python:3.10"
 
 cache:
   paths:
diff --git a/Dockerfile b/Dockerfile
index 446cfc11d3db76d11cb6450e7b9f94fb3c3504c0..4e8a2616e6855fd228438c807cad98177d8ee1d5 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,4 +1,4 @@
-FROM clarinpl/python:3.8
+FROM python:3.10
 
 COPY requirements.txt requirements.txt
 RUN python3 -m pip install -r requirements.txt && rm requirements.txt
diff --git a/Dockerfile.gpu b/Dockerfile.gpu
index 2a530046af413effae3ac6f136e5804bbd3f7c52..ff4cde9da04813c5c33ef1469de69b1d1b171be3 100644
--- a/Dockerfile.gpu
+++ b/Dockerfile.gpu
@@ -1,4 +1,4 @@
-FROM nvidia/cuda:11.7.0-cudnn8-runtime-ubuntu20.04
+FROM nvidia/cuda:11.7.0-cudnn8-runtime-ubuntu22.04
 
 RUN DEBIAN_FRONTEND=noninteractive apt-get update && apt-get install -y gcc python3-dev python3-venv python3-pip
 
diff --git a/requirements-gpu.txt b/requirements-gpu.txt
index cca044f9f9a3d5316255b66dd3fde95903fea1af..3508634c394ab85065b2193ccb822187a688b89b 100644
--- a/requirements-gpu.txt
+++ b/requirements-gpu.txt
@@ -1,4 +1,4 @@
 --index-url https://pypi.clarin-pl.eu/simple/ 
 nlp_ws
-winer==0.2.0
+winer==0.3.0
 awscli==1.22.57
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
index 02e500a4ea74a1822faeb2dd38a4de12645b8cc0..3508634c394ab85065b2193ccb822187a688b89b 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,4 @@
 --index-url https://pypi.clarin-pl.eu/simple/ 
 nlp_ws
+winer==0.3.0
 awscli==1.22.57
\ No newline at end of file
diff --git a/src/winer_worker.py b/src/winer_worker.py
index 7dae252ab3ce5d8ae4bbaf9a01d39530c55036b0..f676237c92b46258becaa54612a89a4347a4b0c1 100644
--- a/src/winer_worker.py
+++ b/src/winer_worker.py
@@ -26,7 +26,7 @@ class WinerWorker:
     ) -> None:
         documents = [create_document_from_clarin_json(read_clarin_json(input_path))]
         outputs = self.active_model.predict(
-            [document.get_pretokenized_text() for document in documents]
+            [str(document) for document in documents]
         )
 
         for idx in range(len(documents)):