tft-pdf / app.py
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feat: pdf extract
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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)