Instructions to use prithivMLmods/Gameplay-Classcode-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Gameplay-Classcode-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Gameplay-Classcode-10") 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/Gameplay-Classcode-10") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Gameplay-Classcode-10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2ef1b9414293d6ffd936b9ee99d9846ec9a288ab5d15fc4614771d9bae0f163
- Size of remote file:
- 372 MB
- SHA256:
- 379eade52d34ea9610b2b926049ddddf3bae5db061ad7564bae5c6d704db749e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.