diff --git a/simulstreaming/translate/hovercraft.py b/simulstreaming/translate/hovercraft.py
index 6e81b68..84ccb28 100644
--- a/simulstreaming/translate/hovercraft.py
+++ b/simulstreaming/translate/hovercraft.py
@@ -57,6 +57,8 @@
     "uk": "Моє судно на повітряній подушці наповнене вуграми.",
     # chatGPT provided:
 #        "uk": "Мій ховеркрафт повний вугрів."
+
+    "he": "הרחפת שלי מלאה בצלופחים.",
 }
 def hovercraft_sentence(lang_code):
     return hovercraft_translations[lang_code]
diff --git a/simulstreaming_translate.py b/simulstreaming_translate.py
index 8f2f155..8d57637 100644
--- a/simulstreaming_translate.py
+++ b/simulstreaming_translate.py
@@ -30,7 +30,7 @@ def generate_words(sp, step_results):
 
 class LLMTranslator:
 
-    def __init__(self, system_prompt='Please translate.', max_context_length=4096, len_ratio=None, model_dir="ct2_EuroLLM-9B-Instruct/", tokenizer_dir="EuroLLM-9B-Instruct/"):
+    def __init__(self, system_prompt='Please translate.', max_context_length=4096, len_ratio=None, model_dir="ct2_EuroLLM-9B-Instruct/", tokenizer_dir="EuroLLM-9B-Instruct/", sys_prompt_in_user=False):
         self.system_prompt = system_prompt
 
         print("Loading the model...", file=sys.stderr)
@@ -46,16 +46,14 @@ def __init__(self, system_prompt='Please translate.', max_context_length=4096, l
 
         # my regex sentence segmenter
         self.segmenter = SentenceSegmenter()
-
-    def start_dialog(self):
-        return [{'role':'system', 'content': self.system_prompt }]
+        self.sys_prompt_in_user = sys_prompt_in_user
 
     def build_prompt(self, dialog):
         # Build prompt with system + user + generation prompt (assistant turn marker),
-        base_toks = self.tokenizer.apply_chat_template(dialog[:2], tokenize=True, add_generation_prompt=True)["input_ids"]
-        if len(dialog) == 3:  # if there is assistant message
+        base_toks = self.tokenizer.apply_chat_template(dialog[:1 if self.sys_prompt_in_user else 2], tokenize=True, add_generation_prompt=True)["input_ids"]
+        if len(dialog) == 2 if self.sys_prompt_in_user else 3:  # if there is assistant message
             # then append the forced assistant content tokens.
-            forced_toks = self.tokenizer.encode(dialog[2]['content'], add_special_tokens=False)
+            forced_toks = self.tokenizer.encode(dialog[-1]['content'], add_special_tokens=False)
             toks = base_toks + forced_toks
         else:
             toks = base_toks
@@ -66,8 +64,11 @@ def build_prompt(self, dialog):
 
     def translate(self, src, tgt_forced=""):
 
-        dialog = self.start_dialog()
-        dialog += [{'role':'user','content': src}]
+        if not self.sys_prompt_in_user:
+            dialog = [{'role':'system', 'content': self.system_prompt },
+                {'role':'user','content': src}]
+        else:
+            dialog = [{'role':'user', 'content': self.system_prompt + "\n\n" + src}]
         if tgt_forced != "":
             dialog += [{'role':'assistant','content': tgt_forced}]
 
@@ -344,7 +345,11 @@ def finish(self):
     "no": "Norwegian",
     "ru": "Russian",
     "tr": "Turkish",
-    "uk": "Ukrainian"
+    "uk": "Ukrainian",
+
+
+    # other languages:
+    "he": "Hebrew",
 }
 
 SrcLang = "English"  # TODO: default parameters.
@@ -400,6 +405,9 @@ def translate_args(parser):
 
     parser.add_argument('--sys_prompt', type=str, default=None, 
                         help='System prompt. If None, default one is used, depending on the language.')
+    parser.add_argument('--sys-in-user', default=False, action="store_true", 
+                        help='Place "system prompt" in use message, e.g. for gemma models.')
+    
 
     parser.add_argument('--init_prompt_src', type=str, default=None, help='Init translation with source text. It should be a complete sentence in the source language. ' 
                         'It can be context specific for the given input. Default is ')
@@ -479,7 +487,7 @@ def simul_translator_factory(args):
         len_threshold = args.len_threshold
 
     llmtrans = LLMTranslator(system_prompt=sys_prompt, max_context_length=args.max_context_length, len_ratio=len_threshold,
-                             model_dir=args.model_dir, tokenizer_dir=args.tokenizer_dir)
+                             model_dir=args.model_dir, tokenizer_dir=args.tokenizer_dir, sys_prompt_in_user=args.sys_in_user)
     lan = args.tgt_lan if not args.tgt_lan.startswith("zh") else "zh"
     simul = SimulLLM(llmtrans,language=lan, min_len=args.min_len, chunk=args.min_chunk_size,
                     init_src=init_src, init_tgt=init_tgt, trimming=args.buffer_trimming