File size: 2,449 Bytes
6332194 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
#!/usr/bin/env python3
"""
T5 Prompt Enhancer V0.3 Demo Script
Quick test of all four instruction types
"""
import torch
from transformers import T5Tokenizer, T5ForConditionalGeneration
def load_model():
"""Load the T5 V0.3 model"""
print("🤖 Loading T5 Prompt Enhancer V0.3...")
tokenizer = T5Tokenizer.from_pretrained(".")
model = T5ForConditionalGeneration.from_pretrained(".")
if torch.cuda.is_available():
model = model.cuda()
print("✅ Model loaded on GPU")
else:
print("✅ Model loaded on CPU")
return model, tokenizer
def enhance_prompt(model, tokenizer, text, style="clean"):
"""Generate enhanced prompt with style control"""
style_prompts = {
"clean": f"Enhance this prompt (no lora): {text}",
"technical": f"Enhance this prompt (with lora): {text}",
"simplify": f"Simplify this prompt: {text}",
"standard": f"Enhance this prompt: {text}"
}
prompt = style_prompts[style]
inputs = tokenizer(prompt, return_tensors="pt", max_length=256, truncation=True)
if torch.cuda.is_available():
inputs = {k: v.cuda() for k, v in inputs.items()}
with torch.no_grad():
outputs = model.generate(
**inputs,
max_length=80,
num_beams=2,
repetition_penalty=2.0,
no_repeat_ngram_size=3,
pad_token_id=tokenizer.pad_token_id
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
def main():
"""Demo all four instruction types"""
# Load model
model, tokenizer = load_model()
# Test prompts
test_prompts = [
"woman in red dress",
"cat on chair",
"cyberpunk cityscape",
"masterpiece, best quality, ultra-detailed render of a fantasy dragon with golden scales"
]
styles = ["standard", "clean", "technical", "simplify"]
print("\n🎨 T5 Prompt Enhancer V0.3 Demo")
print("="*60)
for prompt in test_prompts:
print(f"\n📝 Input: '{prompt}'")
print("-" * 40)
for style in styles:
try:
result = enhance_prompt(model, tokenizer, prompt, style)
print(f"{style:>10}: {result}")
except Exception as e:
print(f"{style:>10}: ERROR - {e}")
print()
if __name__ == "__main__":
main() |