Instructions to use nonsodev/datrix-image-classification-job_98cc84ca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nonsodev/datrix-image-classification-job_98cc84ca with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nonsodev/datrix-image-classification-job_98cc84ca") 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("nonsodev/datrix-image-classification-job_98cc84ca") model = AutoModelForImageClassification.from_pretrained("nonsodev/datrix-image-classification-job_98cc84ca", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d94d7b33944bb6d545b3cac90339f6b598cd62af362f5fbec3017a59abbe7342
- Size of remote file:
- 5.33 kB
- SHA256:
- 1eefe63ec0fc4520909f72cd53772c734d4208b1ee3a9d257a702ac2438b13bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.