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/4c59bd33a00aef477cc1424e2eea085183dc2623/training_args.bin
- Command line
-
hf download hf://djbp/NMM_Classification_base_V10@4c59bd33a00aef477cc1424e2eea085183dc2623/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/djbp/NMM_Classification_base_V10/resolve/4c59bd33a00aef477cc1424e2eea085183dc2623/training_args.bin
4.86 kB
- Xet hash:
- 70944c149718437249ebf3a3659f4c0a5d12754ac1b2bcf616972281814ae54d
- Size of remote file:
- 4.86 kB
- SHA256:
- 49d3eb36cf86c104e768cebf5ddd5e8d9372d55d076b12e76e9f0ca2a0241442
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