diff --git a/TTS/server/server.py b/TTS/server/server.py
index 569b8a21..f1e3813f 100644
--- a/TTS/server/server.py
+++ b/TTS/server/server.py
@@ -1,13 +1,15 @@
 #!flask/bin/python
+from typing import Union
+
 import argparse
 import io
 import os
 import sys
 from pathlib import Path
+import json
 
 from flask import Flask, render_template, request, send_file
 
-from TTS.utils.generic_utils import style_wav_uri_to_dict
 from TTS.utils.io import load_config
 from TTS.utils.manage import ModelManager
 from TTS.utils.synthesizer import Synthesizer
@@ -29,19 +31,27 @@ def create_argparser():
     parser.add_argument(
         "--model_name",
         type=str,
-        default="tts_models/en/ljspeech/speedy-speech-wn",
-        help="name of one of the released tts models.",
+        default="tts_models/en/ljspeech/tacotron2-DDC",
+        help="Name of one of the pre-trained tts models in format <language>/<dataset>/<model_name>",
     )
     parser.add_argument("--vocoder_name", type=str, default=None, help="name of one of the released vocoder models.")
-    parser.add_argument("--tts_checkpoint", type=str, help="path to custom tts checkpoint file")
-    parser.add_argument("--tts_config", type=str, help="path to custom tts config.json file")
+
+     # Args for running custom models
+    parser.add_argument("--config_path", default=None, type=str, help="Path to model config file.")
     parser.add_argument(
-        "--tts_speakers",
+        "--model_path",
         type=str,
-        help="path to JSON file containing speaker ids, if speaker ids are used in the model",
+        default=None,
+        help="Path to model file.",
     )
-    parser.add_argument("--vocoder_config", type=str, default=None, help="path to vocoder config file.")
-    parser.add_argument("--vocoder_checkpoint", type=str, default=None, help="path to vocoder checkpoint file.")
+    parser.add_argument(
+        "--vocoder_path",
+        type=str,
+        help="Path to vocoder model file. If it is not defined, model uses GL as vocoder. Please make sure that you installed vocoder library before (WaveRNN).",
+        default=None,
+    )
+    parser.add_argument("--vocoder_config_path", type=str, help="Path to vocoder model config file.", default=None)
+    parser.add_argument("--speakers_file_path", type=str, help="JSON file for multi-speaker model.", default=None)
     parser.add_argument("--port", type=int, default=5002, help="port to listen on.")
     parser.add_argument("--use_cuda", type=convert_boolean, default=False, help="true to use CUDA.")
     parser.add_argument("--debug", type=convert_boolean, default=False, help="true to enable Flask debug mode.")
@@ -60,26 +70,38 @@ if args.list_models:
     sys.exit()
 
 # update in-use models to the specified released models.
-if args.model_name is not None:
-    tts_checkpoint_file, tts_config_file, tts_json_dict = manager.download_model(args.model_name)
-    args.vocoder_name = tts_json_dict["default_vocoder"] if args.vocoder_name is None else args.vocoder_name
+model_path = None
+config_path = None
+speakers_file_path = None
+vocoder_path = None
+vocoder_config_path = None
 
-if args.vocoder_name is not None:
-    vocoder_checkpoint_file, vocoder_config_file, vocoder_json_dict = manager.download_model(args.vocoder_name)
+# CASE1: list pre-trained TTS models
+if args.list_models:
+    manager.list_models()
+    sys.exit()
 
-# If these were not specified in the CLI args, use default values with embedded model files
-if not args.tts_checkpoint and os.path.isfile(tts_checkpoint_file):
-    args.tts_checkpoint = tts_checkpoint_file
-if not args.tts_config and os.path.isfile(tts_config_file):
-    args.tts_config = tts_config_file
+# CASE2: load pre-trained model paths
+if args.model_name is not None and not args.model_path:
+    model_path, config_path, model_item = manager.download_model(args.model_name)
+    args.vocoder_name = model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name
 
-if not args.vocoder_checkpoint and os.path.isfile(vocoder_checkpoint_file):
-    args.vocoder_checkpoint = vocoder_checkpoint_file
-if not args.vocoder_config and os.path.isfile(vocoder_config_file):
-    args.vocoder_config = vocoder_config_file
+if args.vocoder_name is not None and not args.vocoder_path:
+    vocoder_path, vocoder_config_path, _ = manager.download_model(args.vocoder_name)
 
+# CASE3: set custome model paths
+if args.model_path is not None:
+    model_path = args.model_path
+    config_path = args.config_path
+    speakers_file_path = args.speakers_file_path
+
+if args.vocoder_path is not None:
+    vocoder_path = args.vocoder_path
+    vocoder_config_path = args.vocoder_config_path
+
+# load models
 synthesizer = Synthesizer(
-    args.tts_checkpoint, args.tts_config, args.vocoder_checkpoint, args.vocoder_config, args.use_cuda
+    model_path, config_path, speakers_file_path, vocoder_path, vocoder_config_path, args.use_cuda
 )
 
 use_speaker_embedding = synthesizer.tts_config.get("use_external_speaker_embedding_file", False)
@@ -87,6 +109,26 @@ use_gst = synthesizer.tts_config.get("use_gst", False)
 app = Flask(__name__)
 
 
+def style_wav_uri_to_dict(style_wav: str) -> Union[str, dict]:
+    """Transform an uri style_wav, in either a string (path to wav file to be use for style transfer)
+    or a dict (gst tokens/values to be use for styling)
+
+    Args:
+        style_wav (str): uri
+
+    Returns:
+        Union[str, dict]: path to file (str) or gst style (dict)
+    """
+    if style_wav:
+        if os.path.isfile(style_wav) and style_wav.endswith(".wav"):
+            return style_wav  # style_wav is a .wav file located on the server
+
+        style_wav = json.loads(style_wav)
+        return style_wav  # style_wav is a gst dictionary with {token1_id : token1_weigth, ...}
+    else:
+        return None
+
+
 @app.route("/")
 def index():
     return render_template(