Instructions to use prithivMLmods/Food-101-93M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Food-101-93M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Food-101-93M") 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/Food-101-93M") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Food-101-93M") - Notebooks
- Google Colab
- Kaggle
Training script
#1
by continuous-learning - opened
Hello
Can you please provide the training script for this model ?
Thank you
@continuous-learning
Yeah, sure.
Kindly check out the following page: https://github.com/PRITHIVSAKTHIUR/FineTuning-SigLIP-2/blob/main/Finetune-SigLIP2-Image-Classification/1.SigLIP2_Finetune_ImageClassification_TrainTest_Splits.ipynb
Note: I don't have the exact one, but this is the general script.
Adjust the dataset and its label2id based on your dataset. Happy fine-tuning!