Image Classification
Transformers
Safetensors
English
siglip
Formula-Text-Detection
SigLIP2
Image-Classification
Instructions to use prithivMLmods/Formula-Text-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Formula-Text-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Formula-Text-Detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Formula-Text-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Formula-Text-Detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01efe3cc52d968c241e7b219069130f08b997850b2cd4f9e2c33584541b9b209
- Size of remote file:
- 372 MB
- SHA256:
- 66b18c5dac8d511eac4f0d9d5ef00e55689a973ec03ce3dcb2fb7f4acd03b781
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.