use shared llama

Signed-off-by: Vladimir Mandic <mandic00@live.com>

CHANGELOG.md

@@ -93,7 +93,8 @@
   - **xyz-grid** add guidance section  
   - **preview** implement configurable layers for WAN, Qwen, HV  
 - **Video**
-  - use shared T5 text encoder for video models when possible  
+  - use shared **T5** text encoder for video models when possible  
+  - use shared **LLama** text encoder for video models when possible  
   - unified video save code across all video models  
     also avoids creation of temporary files for each frame unless user wants to save them  
   - unified prompt enhance code across all video models  

modules/video_models/video_load.py

@@ -25,10 +25,17 @@ def load_model(selected: models_def.Model):
     # text encoder
     try:
         load_args, quant_args = model_quant.get_dit_args({}, module='TE', device_map=True)
+
+        # loader deduplication of text-encoder models
         if selected.te_cls.__name__ == 'T5EncoderModel' and shared.opts.te_shared_t5:
             selected.te = 'Disty0/t5-xxl'
             selected.te_folder = ''
             selected.te_revision = None
+        if selected.te_cls.__name__ == 'LlamaModel' and shared.opts.te_shared_t5:
+            selected.te = 'hunyuanvideo-community/HunyuanVideo'
+            selected.te_folder = 'text_encoder'
+            selected.te_revision = None
+
         shared.log.debug(f'Video load: module=te repo="{selected.te or selected.repo}" folder="{selected.te_folder}" cls={selected.te_cls.__name__} quant={model_quant.get_quant_type(quant_args)}')
         kwargs["text_encoder"] = selected.te_cls.from_pretrained(
             pretrained_model_name_or_path=selected.te or selected.repo,