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korea-deep-learning
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Model Details
Model Provider
korea-deep-learning
Model Tree
Qwen/Qwen2.5-VL-7B-Instruct
Input Modalities
Output Modalities
Supported Functionality
This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct specialized for table recognition tasks. The model was trained using LoRA (Low-Rank Adaptation) and then merged with the base model for efficient inference.
Key Features:
merge_and_unload()python
import torchfrom transformers import AutoModelForVision2Seq, AutoProcessorfrom PIL import Image# Load model and processormodel = AutoModelForVision2Seq.from_pretrained("korea-deep-learning/Qwen2.5-VL-7B-TableRecog",torch_dtype=torch.bfloat16,device_map="auto",trust_remote_code=True)processor = AutoProcessor.from_pretrained("korea-deep-learning/Qwen2.5-VL-7B-TableRecog",trust_remote_code=True)# Prepare image and textimage = Image.open("table_image.png")text = "Extract the table content and structure from this image."# Process inputsinputs = processor(text=text, images=image, return_tensors="pt").to(model.device)# Generate outputwith torch.no_grad():outputs = model.generate(**inputs, max_new_tokens=1024)result = processor.decode(outputs[0], skip_special_tokens=True)print(result)
The model has been evaluated on table recognition tasks with the following metrics:
bibtex
@misc{qwen2.5-vl-tablerecog,author = {Korea Deep Learning Team},title = {Qwen2.5-VL-7B-TableRecog: Table Recognition Model},year = {2025},publisher = {HuggingFace},howpublished = {\url{https://huggingface.co/korea-deep-learning/Qwen2.5-VL-7B-TableRecog}},}
This model inherits the Apache 2.0 license from the base Qwen2.5-VL-7B-Instruct model.