Instructions to use sudo-s/exper_batch_32_e8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sudo-s/exper_batch_32_e8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sudo-s/exper_batch_32_e8") 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("sudo-s/exper_batch_32_e8") model = AutoModelForImageClassification.from_pretrained("sudo-s/exper_batch_32_e8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9cf6f0040346f7424aaf46790402a0ffb8adbbf10f7a496d3050490051dc4beb
- Size of remote file:
- 2.94 kB
- SHA256:
- 34a801c59bd0678b3f0a3d44f6cf347c433f68cc44613c7e3d72bf45dfbf78e6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.