Instructions to use james-burton/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use james-burton/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="james-burton/test") 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("james-burton/test") model = AutoModelForImageClassification.from_pretrained("james-burton/test") - Notebooks
- Google Colab
- Kaggle
File size: 1,077 Bytes
3752cdf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | BM pretrain,Train data,Test time method,config,Acc.,Top 3 Acc.,Top 5 Acc.,Top 10 Acc.,F1,Precision,Recall
No,white,avg,om6-white_material,0.603,0.793,0.854,0.911,0.58,0.572,0.603
,,avg+3D,om6-white_material,0.6,0.79,0.856,0.91,0.574,0.568,0.6
,white+3Dx1,avg,om6-3Dwhite-1frame_material,0.578,0.786,0.852,0.915,0.556,0.574,0.578
,,avg+3D,om6-3Dwhite-1frame_material,0.581,0.793,0.858,0.917,0.558,0.58,0.581
,white+3Dx4,avg,om6-3Dwhite_material,0.592,0.795,0.858,0.919,0.57,0.568,0.592
,,avg+3D,om6-3Dwhite_material,0.597,0.793,0.858,0.922,0.571,0.567,0.597
Yes,white,avg,om6-white_material_bm-pretrn,0.612,0.804,0.865,0.917,0.587,0.579,0.612
,,avg+3D,om6-white_material_bm-pretrn,0.613,0.812,0.864,0.922,0.589,0.586,0.613
,white+3Dx1,avg,om6-3Dwhite-1frame_material_bm-pretrn,0.598,0.791,0.864,0.919,0.573,0.566,0.598
,,avg+3D,om6-3Dwhite-1frame_material_bm-pretrn,0.599,0.787,0.863,0.924,0.571,0.568,0.599
,white+3Dx4,avg,om6-3Dwhite_material_bm-pretrn,0.597,0.793,0.859,0.924,0.575,0.575,0.597
,,avg+3D,om6-3Dwhite_material_bm-pretrn,0.609,0.799,0.867,0.927,0.585,0.58,0.609
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