hardbanai, hardbanrecords, audio-generation, text-generation, image-generation, ai-publishing, creative-ai, emotional-style, multimodal, polish-language, musicgen

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HardbanAI / run_inference.py

HardbanRecordsLab

Create run_inference.py

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import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

def main():
    model_path = "./"  # lub ścieżka do folderu z modelem
    print("Ładowanie tokenizera i modelu...")
    tokenizer = AutoTokenizer.from_pretrained(model_path)
    model = AutoModelForSeq2SeqLM.from_pretrained(model_path)

    while True:
        text = input("Wpisz tekst do przetworzenia (lub wpisz 'exit' aby zakończyć): ")
        if text.lower() == "exit":
            print("Koniec.")
            break

        inputs = tokenizer(text, return_tensors="pt")
        outputs = model.generate(**inputs)
        result = tokenizer.decode(outputs[0], skip_special_tokens=True)

        print("Wynik generacji:", result)
        print("-" * 40)

if __name__ == "__main__":
    main()

	import torch
	from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

	def main():
	model_path = "./" # lub ścieżka do folderu z modelem
	print("Ładowanie tokenizera i modelu...")
	tokenizer = AutoTokenizer.from_pretrained(model_path)
	model = AutoModelForSeq2SeqLM.from_pretrained(model_path)

	while True:
	text = input("Wpisz tekst do przetworzenia (lub wpisz 'exit' aby zakończyć): ")
	if text.lower() == "exit":
	print("Koniec.")
	break

	inputs = tokenizer(text, return_tensors="pt")
	outputs = model.generate(**inputs)
	result = tokenizer.decode(outputs[0], skip_special_tokens=True)

	print("Wynik generacji:", result)
	print("-" * 40)

	if __name__ == "__main__":
	main()