Image Classification
Transformers
Safetensors
deit
vision
document-layout-analysis
document-classification
doclaynet
Instructions to use kaixkhazaki/deit_doclaynet_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaixkhazaki/deit_doclaynet_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kaixkhazaki/deit_doclaynet_base") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("kaixkhazaki/deit_doclaynet_base") model = AutoModelForImageClassification.from_pretrained("kaixkhazaki/deit_doclaynet_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from kaixkhazaki/deit_doclaynet_base: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/kaixkhazaki/deit_doclaynet_base/resolve/main/model.safetensors
- Command line
-
hf download hf://kaixkhazaki/deit_doclaynet_base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/kaixkhazaki/deit_doclaynet_base/resolve/main/model.safetensors
343 MB
- Xet hash:
- 2b5d835d70a95f5b246b0c6178f615278b1e3c8b5378fb85d87dbd11a076d353
- Size of remote file:
- 343 MB
- SHA256:
- 7f82df7a54e6ad93368486223f48132be405e1275add362f0ae58a549b9ea75f
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