diff --git a/.github/workflows/build_and_push.yml b/.github/workflows/build_and_push.yml
index 072208b1b6..17ad5c3c8d 100644
--- a/.github/workflows/build_and_push.yml
+++ b/.github/workflows/build_and_push.yml
@@ -1,4 +1,4 @@
-name: Build and Push Docker Images
+name: Build & Push
 
 on:
   push:
@@ -12,7 +12,7 @@ env:
 
 jobs:
   dockerhub:
-    name: Build and push to Docker Hub
+    name: Docker Hub
     runs-on: ubuntu-latest
     steps:
       - name: Check out the repo
@@ -30,8 +30,9 @@ jobs:
       - name: Build and Push Docker Image
         run: make docker
   ecr:
-    name: Build and push to Amazon ECR
+    name: Amazon ECR
     runs-on: ubuntu-latest
+    depends-on: dockerhub
     steps:
       - name: Checkout
         uses: actions/checkout@v4
@@ -42,7 +43,6 @@ jobs:
           aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
           aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
           aws-region: ${{ env.AWS_REGION }}
-          role-to-assume: ${{ secrets.AWS_ROLE }}
 
       - name: Login to Amazon ECR
         id: login-ecr
diff --git a/src/autotrain/backend.py b/src/autotrain/backend.py
index bc7d5d7c19..5bbfc4ddb5 100644
--- a/src/autotrain/backend.py
+++ b/src/autotrain/backend.py
@@ -160,93 +160,6 @@ def _dreambooth_munge_data(params, username):
     return params.image_path
 
 
-@dataclass
-class EndpointsRunner:
-    params: Union[TextClassificationParams, ImageClassificationParams, LLMTrainingParams]
-    backend: str
-
-    def __post_init__(self):
-        self.endpoints_backends = {
-            "ep-aws-useast1-s": "aws_us-east-1_gpu_small_g4dn.xlarge",
-            "ep-aws-useast1-m": "aws_us-east-1_gpu_medium_g5.2xlarge",
-            "ep-aws-useast1-l": "aws_us-east-1_gpu_large_g4dn.12xlarge",
-            "ep-aws-useast1-xl": "aws_us-east-1_gpu_xlarge_p4de",
-            "ep-aws-useast1-2xl": "aws_us-east-1_gpu_2xlarge_p4de",
-            "ep-aws-useast1-4xl": "aws_us-east-1_gpu_4xlarge_p4de",
-            "ep-aws-useast1-8xl": "aws_us-east-1_gpu_8xlarge_p4de",
-        }
-        if self.params.repo_id is not None:
-            self.username = self.params.repo_id.split("/")[0]
-        elif self.params.username is not None:
-            self.username = self.params.username
-        else:
-            raise ValueError("Must provide either repo_id or username")
-        self.api_url = f"https://api.endpoints.huggingface.cloud/v2/endpoint/{self.username}"
-        if isinstance(self.params, LLMTrainingParams):
-            self.task_id = 9
-
-    def _create_endpoint(self):
-        hardware = self.endpoints_backends[self.backend]
-        accelerator = hardware.split("_")[2]
-        instance_size = hardware.split("_")[3]
-        region = hardware.split("_")[1]
-        vendor = hardware.split("_")[0]
-        instance_type = hardware.split("_")[4]
-        payload = {
-            "accountId": self.username,
-            "compute": {
-                "accelerator": accelerator,
-                "instanceSize": instance_size,
-                "instanceType": instance_type,
-                "scaling": {"maxReplica": 1, "minReplica": 1},
-            },
-            "model": {
-                "framework": "custom",
-                "image": {
-                    "custom": {
-                        "env": {
-                            "HF_TOKEN": self.params.token,
-                            "AUTOTRAIN_USERNAME": self.username,
-                            "PROJECT_NAME": self.params.project_name,
-                            "PARAMS": self.params.model_dump_json(),
-                            "DATA_PATH": self.params.data_path,
-                            "TASK_ID": str(self.task_id),
-                            "MODEL": self.params.model,
-                            "OUTPUT_MODEL_REPO": self.params.repo_id,
-                            "ENDPOINT_ID": f"{self.username}/{self.params.project_name}",
-                        },
-                        "health_route": "/",
-                        "port": 7860,
-                        "url": "public.ecr.aws/z4c3o6n6/autotrain:latest",
-                    }
-                },
-                "repository": "autotrain-projects/autotrain-advanced",
-                "revision": "main",
-                "task": "custom",
-            },
-            "name": self.params.project_name,
-            "provider": {"region": region, "vendor": vendor},
-            "type": "protected",
-        }
-        headers = {"Authorization": f"Bearer {self.params.token}"}
-        r = requests.post(self.api_url, json=payload, headers=headers)
-        logger.info(r.json())
-        return r.json()
-
-    def prepare(self):
-        if isinstance(self.params, LLMTrainingParams):
-            data_path = _llm_munge_data(self.params, self.username)
-            self.params.data_path = data_path
-            endpoint_id = self._create_endpoint()
-            return endpoint_id
-        if isinstance(self.params, TextClassificationParams):
-            data_path = _text_clf_munge_data(self.params, self.username)
-            self.params.data_path = data_path
-            endpoint_id = self._create_endpoint()
-            return endpoint_id
-        raise NotImplementedError
-
-
 @dataclass
 class SpaceRunner:
     params: Union[
@@ -410,7 +323,7 @@ def _create_endpoint(self):
                         },
                         "health_route": "/",
                         "port": 7860,
-                        "url": "public.ecr.aws/z4c3o6n6/autotrain:latest",
+                        "url": "public.ecr.aws/z4c3o6n6/autotrain-api:latest",
                     }
                 },
                 "repository": "autotrain-projects/autotrain-advanced",