Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use djbp/NMM_Classification_base_V10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djbp/NMM_Classification_base_V10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="djbp/NMM_Classification_base_V10") 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("djbp/NMM_Classification_base_V10") model = AutoModelForImageClassification.from_pretrained("djbp/NMM_Classification_base_V10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from djbp/NMM_Classification_base_V10: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/djbp/NMM_Classification_base_V10/resolve/c8ca53ba3cb4e4fa6c0e05d3be18b03e5810ef50/training_args.bin
- Command line
-
hf download hf://djbp/NMM_Classification_base_V10@c8ca53ba3cb4e4fa6c0e05d3be18b03e5810ef50/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/djbp/NMM_Classification_base_V10/resolve/c8ca53ba3cb4e4fa6c0e05d3be18b03e5810ef50/training_args.bin
4.86 kB
- Xet hash:
- 3589b55933326a2ecde883c075c6ecd8c622faf263b67ec26b657400a806ddf3
- Size of remote file:
- 4.86 kB
- SHA256:
- 2dc424e708e91b2cbc5081fa54bcfe52a86c68bcb4c667198257b87ea1cb5e40
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