Image-to-Text
PEFT
Safetensors
Portuguese
English
vision-language
table-extraction
scientific-figures
markdown-table
qwen2.5-vl
lora
icdar-metric-loss
Instructions to use lucasoc/sci-image-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lucasoc/sci-image-models with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct") model = PeftModel.from_pretrained(base_model, "lucasoc/sci-image-models") - Notebooks
- Google Colab
- Kaggle
File size: 316 Bytes
be90b31 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | """
Model loading and architecture wrappers.
"""
from .loader import load_model_and_processor, build_peft_config, build_quantization_config
from .qwen_vl import QwenVLTableExtractor
__all__ = [
"load_model_and_processor",
"build_peft_config",
"build_quantization_config",
"QwenVLTableExtractor",
]
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