diff --git a/__init__.py b/__init__.py
index b57095a..80c83b2 100644
--- a/__init__.py
+++ b/__init__.py
@@ -7,8 +7,18 @@ Generate complete songs with vocals and instrumentals from lyrics!
 
 import sys
 import os
+import warnings
 import importlib.util
 
+# Suppress cosmetic warnings from transformers about GenerationMixin and checkpointing format
+# These need to be set early, before transformers is imported
+warnings.filterwarnings("ignore", message=".*GenerationMixin.*")
+warnings.filterwarnings("ignore", message=".*old version of the checkpointing format.*")
+warnings.filterwarnings("ignore", message=".*doesn't directly inherit from.*")
+warnings.filterwarnings("ignore", message=".*will NOT inherit from.*")
+warnings.filterwarnings("ignore", message=".*_set_gradient_checkpointing.*")
+warnings.filterwarnings("ignore", category=FutureWarning, module="transformers.*")
+
 # Get current directory
 current_dir = os.path.dirname(os.path.abspath(__file__))
 
diff --git a/codeclm/models/codeclm.py b/codeclm/models/codeclm.py
index d0304f4..53deb46 100644
--- a/codeclm/models/codeclm.py
+++ b/codeclm/models/codeclm.py
@@ -139,6 +139,14 @@ class CodecLM:
             bgm_wavs = list(bgm_wavs)
         
         texts, audio_qt_embs = self._prepare_tokens_and_attributes(lyrics=lyrics, melody_wavs=melody_wavs, vocal_wavs=vocal_wavs, bgm_wavs=bgm_wavs, melody_is_wav=melody_is_wav)
+
+        # Debug: Log what's being passed to _generate_tokens
+        print(f"\n[CodecLM DEBUG] ========== _generate_tokens INPUT ==========")
+        print(f"[CodecLM DEBUG] texts (lyrics): {texts}")
+        print(f"[CodecLM DEBUG] descriptions: {descriptions}")
+        print(f"[CodecLM DEBUG] audio_qt_embs shape: {audio_qt_embs.shape if audio_qt_embs is not None else 'None'}")
+        print(f"[CodecLM DEBUG] ================================================\n")
+
         tokens = self._generate_tokens(texts, descriptions, audio_qt_embs)
 
         if (tokens == self.lm.eos_token_id).any():
diff --git a/codeclm/models/lm_levo.py b/codeclm/models/lm_levo.py
index c851fb7..d5bba18 100755
--- a/codeclm/models/lm_levo.py
+++ b/codeclm/models/lm_levo.py
@@ -233,7 +233,13 @@ class LmModel(StreamingModule):
                     if descriptions is not None:
                         attr["text"]["type_info"] = descriptions[i]
                 conditions.append(attr)
-                print("conditions", conditions)
+                # Enhanced debug logging for lyrics/descriptions
+                print(f"\n[LmLevo DEBUG] ========== CONDITION ATTRIBUTES ==========")
+                print(f"[LmLevo DEBUG] Available conditioners: {list(self.condition_provider.conditioners.keys())}")
+                print(f"[LmLevo DEBUG] attr['text']['description'] (LYRICS): {repr(attr.text.get('description', 'NOT SET'))[:200]}")
+                print(f"[LmLevo DEBUG] attr['text']['type_info'] (DESCRIPTION): {repr(attr.text.get('type_info', 'NOT SET'))[:200]}")
+                print(f"[LmLevo DEBUG] Has prompt_audio: {'prompt_audio' in attr.audio}")
+                print(f"[LmLevo DEBUG] =============================================\n")
             if prepare_null_condition:
                 cfg_inference = ClassifierFreeGuidanceDropoutInference() 
                 null_conditions = cfg_inference(conditions, condition_types=["audio", "text"], 
diff --git a/codeclm/modules/conditioners.py b/codeclm/modules/conditioners.py
index 7a66fe8..cee65aa 100755
--- a/codeclm/modules/conditioners.py
+++ b/codeclm/modules/conditioners.py
@@ -133,9 +133,22 @@ class QwTokenizerConditioner(TextConditioner):
         print("all structure tokens: ", {self.text_tokenizer.convert_ids_to_tokens(i):i for i in self.struct_token_ids})
         
     def tokenize(self, x: tp.List[tp.Optional[str]]) -> tp.Dict[str, torch.Tensor]:
+        # Debug: Log input before tokenization
+        print(f"\n[QwTokenizerConditioner DEBUG] ========== TOKENIZE INPUT ==========")
+        print(f"[QwTokenizerConditioner DEBUG] Input text (first item, first 300 chars): {repr(x[0][:300]) if x and x[0] else 'None/Empty'}")
+        print(f"[QwTokenizerConditioner DEBUG] Number of inputs: {len(x)}")
+
         x = ['<|im_start|>' + xi if xi is not None else "<|im_start|>" for xi in x]
         # x = [xi if xi is not None else "" for xi in x]
         inputs = self.text_tokenizer(x, return_tensors="pt", padding=True)
+
+        # Debug: Log tokenization result
+        print(f"[QwTokenizerConditioner DEBUG] Tokenized shape: {inputs['input_ids'].shape}")
+        print(f"[QwTokenizerConditioner DEBUG] First 20 token IDs: {inputs['input_ids'][0][:20].tolist()}")
+        decoded = self.text_tokenizer.decode(inputs['input_ids'][0][:50])
+        print(f"[QwTokenizerConditioner DEBUG] Decoded first 50 tokens: {repr(decoded)}")
+        print(f"[QwTokenizerConditioner DEBUG] ===========================================\n")
+
         return inputs
 
     def forward(self, inputs: tp.Dict[str, torch.Tensor]) -> ConditionType:
diff --git a/fl_nodes/lyrics_formatter.py b/fl_nodes/lyrics_formatter.py
index ea5211d..7e7869c 100644
--- a/fl_nodes/lyrics_formatter.py
+++ b/fl_nodes/lyrics_formatter.py
@@ -3,8 +3,21 @@ FL Song Gen Lyrics Formatter Node.
 Helps users build properly formatted lyrics with section tags.
 """
 
+import re
 from typing import Tuple
 
+# Regex to filter lyrics - keeps letters, numbers, whitespace, brackets, hyphens, and CJK characters
+# Removes punctuation like commas, apostrophes, quotes, etc.
+LYRICS_FILTER_REGEX = re.compile(
+    r"[^\w\s\[\]\-\u4e00-\u9fff\u3040-\u309f\u30a0-\u30ff\uac00-\ud7af\u00c0-\u017f]"
+)
+
+
+def clean_lyrics_line(line: str) -> str:
+    """Clean a single lyrics line by removing unsupported punctuation."""
+    cleaned = LYRICS_FILTER_REGEX.sub("", line)
+    return cleaned.strip()
+
 
 class FL_SongGen_LyricsFormatter:
     """
@@ -228,9 +241,14 @@ class FL_SongGen_LyricsFormatter:
         """
         Convert multiline text to SongGen format.
         Newlines become periods to separate phrases.
+        Punctuation is removed to match model training data format.
         """
-        # Split by newlines, strip each line, filter empty
-        lines = [line.strip() for line in text.strip().split("\n") if line.strip()]
+        # Split by newlines, clean each line, filter empty
+        lines = []
+        for line in text.strip().split("\n"):
+            cleaned = clean_lyrics_line(line)
+            if cleaned:
+                lines.append(cleaned)
 
-        # Join with period-space (matches original SongGeneration training data format)
-        return ". ".join(lines)
+        # Join with period only (matches official SongGeneration format)
+        return ".".join(lines)
diff --git a/fl_utils/model_manager.py b/fl_utils/model_manager.py
index 02b203b..b0e7a95 100644
--- a/fl_utils/model_manager.py
+++ b/fl_utils/model_manager.py
@@ -19,6 +19,10 @@ from omegaconf import OmegaConf
 # Suppress cosmetic warnings from transformers about GenerationMixin and checkpointing format
 warnings.filterwarnings("ignore", message=".*GenerationMixin.*")
 warnings.filterwarnings("ignore", message=".*old version of the checkpointing format.*")
+warnings.filterwarnings("ignore", message=".*doesn't directly inherit from.*")
+warnings.filterwarnings("ignore", message=".*will NOT inherit from.*")
+warnings.filterwarnings("ignore", message=".*_set_gradient_checkpointing.*")
+warnings.filterwarnings("ignore", category=FutureWarning, module="transformers.*")
 
 # Get the fl_utils directory (same directory as this file)
 _FL_UTILS_DIR = os.path.dirname(__file__)
diff --git a/fl_utils/songgen_wrapper.py b/fl_utils/songgen_wrapper.py
index 222b8b9..f74ba5c 100644
--- a/fl_utils/songgen_wrapper.py
+++ b/fl_utils/songgen_wrapper.py
@@ -5,6 +5,7 @@ Encapsulates the inference logic from SongGeneration's generate.py.
 
 import gc
 import os
+import re
 import sys
 import tempfile
 import importlib.util
@@ -15,6 +16,12 @@ import torch
 import torchaudio
 import soundfile as sf
 
+# Regex to filter lyrics - keeps letters, numbers, whitespace, brackets, hyphens, and CJK characters
+# Removes punctuation like commas, apostrophes, quotes, etc. that the model wasn't trained on
+LYRICS_FILTER_REGEX = re.compile(
+    r"[^\w\s\[\]\-;\.\u4e00-\u9fff\u3040-\u309f\u30a0-\u30ff\uac00-\ud7af\u00c0-\u017f]"
+)
+
 # Get the fl_utils directory (same directory as this file)
 _FL_UTILS_DIR = os.path.dirname(__file__)
 
@@ -112,8 +119,9 @@ class SongGenWrapper:
             print(f"[FL SongGen] Duration {duration}s exceeds max {self.max_duration}s, clamping.")
             duration = self.max_duration
 
-        # Clean lyrics
-        lyrics = lyrics.replace("  ", " ")
+        # Clean lyrics - remove unsupported punctuation and normalize spaces
+        lyrics = LYRICS_FILTER_REGEX.sub("", lyrics)
+        lyrics = re.sub(r"\s+", " ", lyrics)  # Normalize multiple spaces to single space
 
         if self.low_mem:
             return self._generate_lowmem(
@@ -193,6 +201,16 @@ class SongGenWrapper:
             'melody_is_wav': melody_is_wav,
         }
 
+        # Debug: Log what we're passing to the model
+        print(f"\n[FL SongGen DEBUG] ========== GENERATION INPUT ==========")
+        print(f"[FL SongGen DEBUG] Lyrics (first 200 chars): {repr(lyrics[:200]) if lyrics else 'None'}")
+        print(f"[FL SongGen DEBUG] Description: {repr(description) if description else 'None'}")
+        print(f"[FL SongGen DEBUG] melody_wavs shape: {pmt_wav.shape if pmt_wav is not None else 'None'}")
+        print(f"[FL SongGen DEBUG] vocal_wavs shape: {vocal_wav.shape if vocal_wav is not None else 'None'}")
+        print(f"[FL SongGen DEBUG] bgm_wavs shape: {bgm_wav.shape if bgm_wav is not None else 'None'}")
+        print(f"[FL SongGen DEBUG] melody_is_wav: {melody_is_wav}")
+        print(f"[FL SongGen DEBUG] ======================================\n")
+
         print(f"[FL SongGen] Generating tokens for {duration}s song...")
 
         with torch.autocast(device_type="cuda", dtype=torch.float16, enabled=self.device == "cuda"):
@@ -359,6 +377,16 @@ class SongGenWrapper:
             'melody_is_wav': melody_is_wav,
         }
 
+        # Debug: Log what we're passing to the model (low mem path)
+        print(f"\n[FL SongGen LowMem DEBUG] ========== GENERATION INPUT ==========")
+        print(f"[FL SongGen LowMem DEBUG] Lyrics (first 200 chars): {repr(lyrics[:200]) if lyrics else 'None'}")
+        print(f"[FL SongGen LowMem DEBUG] Description: {repr(description) if description else 'None'}")
+        print(f"[FL SongGen LowMem DEBUG] melody_wavs shape: {pmt_wav.shape if pmt_wav is not None else 'None'}")
+        print(f"[FL SongGen LowMem DEBUG] vocal_wavs shape: {vocal_wav.shape if vocal_wav is not None else 'None'}")
+        print(f"[FL SongGen LowMem DEBUG] bgm_wavs shape: {bgm_wav.shape if bgm_wav is not None else 'None'}")
+        print(f"[FL SongGen LowMem DEBUG] melody_is_wav: {melody_is_wav}")
+        print(f"[FL SongGen LowMem DEBUG] ======================================\n")
+
         print(f"[FL SongGen LowMem] Generating tokens...")
         with torch.autocast(device_type="cuda", dtype=torch.float16):
             with torch.no_grad():
diff --git a/pyproject.toml b/pyproject.toml
index 6328a32..8ff7a91 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "comfyui_fl-songgen"
 description = "FL Song Gen - AI-powered song generation nodes for ComfyUI. Generate complete songs with vocals and instrumentals from lyrics using Tencent's SongGeneration (LeVo) model. Features style transfer, auto style presets, dual-track output, and up to 4m30s song generation."
-version = "1.0.8"
+version = "1.0.9"
 license = "Apache-2.0"
 dependencies = [
     "torch>=2.0.0",