File size: 2,219 Bytes
be90b31 | 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 | # Standalone inference example using the Hugging Face adapter
import torch
from PIL import Image
from transformers import AutoProcessor, Qwen2_5_VLForConditionalGeneration, BitsAndBytesConfig
from peft import PeftModel
from qwen_vl_utils import process_vision_info
import sys
def main(image_path: str, adapter_id: str = "."):
model_id = "Qwen/Qwen2.5-VL-3B-Instruct"
print(f"Loading processor for {adapter_id}...")
processor = AutoProcessor.from_pretrained(adapter_id)
print("Loading base model in 4-bit...")
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.float16,
bnb_4bit_use_double_quant=True,
)
base_model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
model_id,
quantization_config=bnb_config,
torch_dtype=torch.float16,
device_map="auto"
)
print("Loading PEFT LoRA adapter...")
model = PeftModel.from_pretrained(base_model, adapter_id)
model.eval()
image = Image.open(image_path).convert("RGB")
messages = [
{
"role": "user",
"content": [
{"type": "image", "image": image},
{"type": "text", "text": "Extract the plotted quantitative data into a clean Markdown table with column headers."}
]
}
]
text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
image_inputs, _ = process_vision_info(messages)
inputs = processor(text=[text], images=image_inputs, padding=True, return_tensors="pt").to("cuda")
with torch.inference_mode():
generated_ids = model.generate(**inputs, max_new_tokens=1024, temperature=0.0)
generated_ids_trimmed = [
out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
]
output_text = processor.batch_decode(
generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
)[0]
print("\n=== Extracted Markdown Table ===\n")
print(output_text)
if __name__ == "__main__":
img = sys.argv[1] if len(sys.argv) > 1 else "figure.png"
main(img)
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