Instructions to use LuGot16/spermatogenesis-classifier-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LuGot16/spermatogenesis-classifier-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="LuGot16/spermatogenesis-classifier-v2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("LuGot16/spermatogenesis-classifier-v2") model = AutoModelForImageClassification.from_pretrained("LuGot16/spermatogenesis-classifier-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0c9c7b9aa50701dd0c511b3a0e781423d7e6bbaf120fae36cfc35d10dc494bb
- Size of remote file:
- 5.33 kB
- SHA256:
- 9b3b4bec63bbeb61a04d24b768418a994939543bd7354dc05ee3abc19ff8c85e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.