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")# 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
| { | |
| "epoch": 6.892307692307693, | |
| "total_flos": 4.4565045535859466e+18, | |
| "train_loss": 0.45718009237732204, | |
| "train_runtime": 12452.0227, | |
| "train_samples_per_second": 4.634, | |
| "train_steps_per_second": 0.009 | |
| } |