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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,073 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,om3-white_material,0.582,0.782,0.85,0.914,0.553,0.578,0.582
,,avg+3D,om3-white_material,0.576,0.784,0.85,0.92,0.543,0.572,0.576
,white+3Dx1,avg,om3-3Dwhite-1frame_material,0.573,0.759,0.838,0.91,0.555,0.558,0.573
,,avg+3D,om3-3Dwhite-1frame_material,0.567,0.762,0.84,0.915,0.548,0.556,0.567
,white+3Dx4,avg,om3-3Dwhite_material,0.575,0.777,0.843,0.912,0.557,0.561,0.575
,,avg+3D,om3-3Dwhite_material,0.583,0.779,0.849,0.912,0.563,0.565,0.583
Yes,white,avg,om3-white_material_bm-pretrn,0.587,0.787,0.856,0.917,0.555,0.551,0.587
,,avg+3D,om3-white_material_bm-pretrn,0.596,0.797,0.867,0.922,0.566,0.571,0.596
,white+3Dx1,avg,om3-3Dwhite-1frame_material_bm-pretrn,0.59,0.8,0.861,0.925,0.571,0.566,0.59
,,avg+3D,om3-3Dwhite-1frame_material_bm-pretrn,0.59,0.79,0.852,0.918,0.578,0.583,0.59
,white+3Dx4,avg,om3-3Dwhite_material_bm-pretrn,0.582,0.778,0.85,0.911,0.562,0.56,0.582
,,avg+3D,om3-3Dwhite_material_bm-pretrn,0.583,0.779,0.841,0.913,0.572,0.581,0.583
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