Image-to-Text
PEFT
Safetensors
Portuguese
English
vision-language
table-extraction
scientific-figures
markdown-table
lightonocr
qwen2.5-vl
qwen3-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: 179 Bytes
be90b31 | 1 2 3 4 5 6 7 8 9 10 11 | """
Training pipeline modules.
"""
from .trainer import SciImageTableTrainer, build_training_arguments
__all__ = [
"SciImageTableTrainer",
"build_training_arguments",
]
|