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import requests | |
from PIL import Image | |
from transformers import AutoProcessor, AutoModelForCausalLM | |
model = AutoModelForCausalLM.from_pretrained( | |
"yifeihu/TFT-ID-1.0", trust_remote_code=True | |
) | |
processor = AutoProcessor.from_pretrained("yifeihu/TFT-ID-1.0", trust_remote_code=True) | |
prompt = "<OD>" | |
url = "https://huggingface.co/yifeihu/TF-ID-base/resolve/main/arxiv_2305_10853_5.png?download=true" | |
image = Image.open(requests.get(url, stream=True).raw) | |
inputs = processor(text=prompt, images=image, return_tensors="pt") | |
generated_ids = model.generate( | |
input_ids=inputs["input_ids"], | |
pixel_values=inputs["pixel_values"], | |
max_new_tokens=1024, | |
do_sample=False, | |
num_beams=3, | |
) | |
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0] | |
parsed_answer = processor.post_process_generation( | |
generated_text, task="<OD>", image_size=(image.width, image.height) | |
) | |
print(parsed_answer) | |