From ba7120dfc62f31ea64f7a4655e3c7ac120fd0de4 Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Tue, 22 Apr 2025 12:14:37 -0400
Subject: [PATCH] prompt enhancer loader fix

Signed-off-by: Vladimir Mandic <mandic00@live.com>
---
 scripts/prompt_enhance.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/scripts/prompt_enhance.py b/scripts/prompt_enhance.py
index bbc52b0be..d2b4dff2a 100644
--- a/scripts/prompt_enhance.py
+++ b/scripts/prompt_enhance.py
@@ -28,6 +28,11 @@ class Options:
         'cognitivecomputations/Dolphin3.0-Llama3.2-1B': {},
         'cognitivecomputations/Dolphin3.0-Llama3.2-3B': {},
         'nidum/Nidum-Gemma-3-4B-it-Uncensored': {},
+        # 'llava/Llama-3-8B-v1.1-Extracted': {
+        #     'repo': 'hunyuanvideo-community/HunyuanVideo',
+        #     'subfolder': 'text_encoder',
+        #     'tokenizer': 'tokenizer',
+        # },
         'mradermacher/Llama-3.2-1B-Instruct-Uncensored-i1-GGUF': {
             'repo': 'meta-llama/Llama-3.2-1B-Instruct', # original repo so we can load missing components
             'type': 'llama', # required so gguf loader knows what to do
@@ -76,6 +81,8 @@ class Script(scripts.Script):
         model_gguf = model_gguf or self.options.models.get(name, {}).get('gguf', None) or model_repo
         model_type = model_type or self.options.models.get(name, {}).get('type', None)
         model_file = model_file or self.options.models.get(name, {}).get('file', None)
+        model_subfolder = self.options.models.get(name, {}).get('subfolder', None)
+        model_tokenizer = self.options.models.get(name, {}).get('tokenizer', None)
 
         gguf_args = {}
         if model_type is not None and model_file is not None and len(model_type) > 2 and len(model_file) > 2:
@@ -99,6 +106,7 @@ class Script(scripts.Script):
             self.model = None
             self.llm = transformers.AutoModelForCausalLM.from_pretrained(
                 pretrained_model_name_or_path=model_repo if not gguf_args else model_gguf,
+                subfolder=model_subfolder,
                 trust_remote_code=True,
                 torch_dtype=devices.dtype,
                 cache_dir=shared.opts.hfcache_dir,
@@ -109,6 +117,7 @@ class Script(scripts.Script):
             self.llm.eval()
             self.tokenizer = transformers.AutoTokenizer.from_pretrained(
                 pretrained_model_name_or_path=model_repo,
+                subfolder=model_tokenizer,
                 cache_dir=shared.opts.hfcache_dir,
             )
             if debug_enabled: