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
Download training_args.bin from lucasoc/sci-image-models: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/lucasoc/sci-image-models/resolve/main/training_args.bin
- Command line
-
hf download hf://lucasoc/sci-image-models/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lucasoc/sci-image-models/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- 17476bafa3cdd36e487b1a15326ef6625cfdbcfd653b67b69c3544176a8666e2
- Size of remote file:
- 4.79 kB
- SHA256:
- d2e4482c1d43d1a7aec798143001e7972cd7a0f5a767d5da53f2cf051d81e8fc
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