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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 367abef36d1af7296923679b8f6e5c4b14576a252f90c6b4b810c1144e1127b1
- Size of remote file:
- 1.06 kB
- SHA256:
- 46d020344d4cdb625fa3ccdabe828dfdae277b492bb5282dbb9f16edd7c73161
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.