nodes/olivv-cs-ComfyUI-FunPack
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can transformers just stop breaking my code ffs

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This commit is contained in:
aimfordeb
2026-01-30 16:55:20 +02:00
committed by GitHub
parent e64d0405e2
commit 85545ca9e6
1 changed files with 6 additions and 5 deletions
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funpack.py
+6 -5
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@@ -562,7 +562,7 @@ class FunPackPromptEnhancer:
pad_token_id=llm_tokenizer.pad_token_id
)
output_text = llm_tokenizer.decode(generated_ids[0][llm_tokens.shape[1]:], skip_special_tokens=True)
output_text = llm_tokenizer.decode(generated_ids[0][llm_tokens['input_ids'].shape[1]:], skip_special_tokens=True)
print(f"[FunPackPromptEnhancer] Enhanced prompt generated: {output_text}")
return (output_text,)
@@ -683,7 +683,7 @@ class FunPackStoryWriter:
eos_token_id=llm_tokenizer.eos_token_id,
)
story = llm_tokenizer.decode(generated_ids[0][llm_tokens.shape[1]:], skip_special_tokens=True).strip()
story = llm_tokenizer.decode(generated_ids[0][llm_tokens['input_ids'].shape[1]:], skip_special_tokens=True).strip()
print(f"[FunPackStoryWriter] Hidden story: {story[:150]}...")
messages.append({"role": "assistant", "content": story})
@@ -721,7 +721,7 @@ class FunPackStoryWriter:
eos_token_id=llm_tokenizer.eos_token_id,
)
seq_text = llm_tokenizer.decode(generated_ids[0][llm_tokens.shape[1]:], skip_special_tokens=True).strip()
seq_text = llm_tokenizer.decode(generated_ids[0][llm_tokens['input_ids'].shape[1]:], skip_special_tokens=True).strip()
if sanity_check == False:
print(f"[FunPackStoryWriter] Sequence {seq_idx + 1} (sanity check skipped): {seq_text}...")
@@ -763,7 +763,7 @@ class FunPackStoryWriter:
eos_token_id=llm_tokenizer.eos_token_id,
)
seq_text = llm_tokenizer.decode(generated_ids[0][llm_tokens.shape[1]:], skip_special_tokens=True).strip()
seq_text = llm_tokenizer.decode(generated_ids[0][llm_tokens['input_ids'].shape[1]:], skip_special_tokens=True).strip()
print(f"[FunPackStoryWriter] Sequence {seq_idx + 1} (sanity check performed): {seq_text}...")
outputs[seq_idx] = seq_text
@@ -798,7 +798,7 @@ class FunPackStoryWriter:
eos_token_id=llm_tokenizer.eos_token_id,
)
recommended_loras = llm_tokenizer.decode(generated_ids[0][llm_tokens.shape[1]:], skip_special_tokens=True).strip()
recommended_loras = llm_tokenizer.decode(generated_ids[0][llm_tokens['input_ids'].shape[1]:], skip_special_tokens=True).strip()
print(f"[FunPackStoryWriter] LLM recommended to use this list of LoRAs: {recommended_loras}")
return tuple(outputs)
@@ -1457,5 +1457,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {