18 lines
772 B
Python
18 lines
772 B
Python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from PIL import Image
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def run_inference(image_path=None, prompt="Explain the reasoning behind this step-by-step."):
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model_id = "Dev4285/MiniArt-2.0"
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print(f"Loading {model_id}...")
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
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outputs = model.generate(**inputs, max_new_tokens=256)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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if __name__ == "__main__":
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result = run_inference(prompt="What is 15 * 14?")
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print(result)
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