Instructions to use Nicole-M/Dataset2-FastViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use Nicole-M/Dataset2-FastViT with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("Nicole-M/Dataset2-FastViT") - Notebooks
- Google Colab
- Kaggle
This model is a fine-tuned version of FastViT on the Mammogram V1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8279
- Accuracy: 0.5893
Model description
More information needed
Intended uses & limitations
More information needed
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
Training and evaluation data
Framework Versions
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- FastAi
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("Nicole-M/Dataset2-FastViT")