Instructions to use AmineAllo/margin-element-detector-fm-sandy-dragon-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmineAllo/margin-element-detector-fm-sandy-dragon-14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AmineAllo/margin-element-detector-fm-sandy-dragon-14")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("AmineAllo/margin-element-detector-fm-sandy-dragon-14") model = AutoModelForObjectDetection.from_pretrained("AmineAllo/margin-element-detector-fm-sandy-dragon-14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Amine commited on
Commit ·
4304445
1
Parent(s): 2f64ab8
Training in progress, step 2500
Browse files- config.json +54 -0
- preprocessor_config.json +24 -0
- pytorch_model.bin +3 -0
- training_args.bin +3 -0
config.json
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{
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"_name_or_path": "toobiza/MT-ancient-spaceship-83",
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"activation_dropout": 0.0,
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"activation_function": "relu",
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"architectures": [
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"TableTransformerForObjectDetection"
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],
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"attention_dropout": 0.0,
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"auxiliary_loss": false,
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"backbone": "resnet18",
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"backbone_config": null,
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"bbox_cost": 5,
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"bbox_loss_coefficient": 5,
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"ce_loss_coefficient": 1,
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"class_cost": 1,
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"d_model": 256,
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"decoder_attention_heads": 8,
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"decoder_ffn_dim": 2048,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 6,
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"dice_loss_coefficient": 1,
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"dilation": false,
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"dropout": 0.1,
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"encoder_attention_heads": 8,
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"encoder_ffn_dim": 2048,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 6,
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"eos_coefficient": 0.4,
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"giou_cost": 2,
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"giou_loss_coefficient": 2,
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"id2label": {
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"1": "words",
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"2": "no object"
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},
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"init_std": 0.02,
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"init_xavier_std": 1.0,
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"is_encoder_decoder": true,
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"label2id": {
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"no object": 2,
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"words": 1
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},
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"mask_loss_coefficient": 1,
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"max_position_embeddings": 1024,
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"model_type": "table-transformer",
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"num_channels": 3,
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"num_hidden_layers": 6,
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"num_queries": 15,
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"position_embedding_type": "sine",
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"scale_embedding": false,
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"torch_dtype": "float32",
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"transformers_version": "4.33.2",
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"use_pretrained_backbone": true,
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"use_timm_backbone": true
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}
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_pad": true,
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"do_rescale": true,
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"do_resize": true,
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"format": "coco_detection",
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "DetrImageProcessor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"longest_edge": 800,
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"shortest_edge": 800
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}
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:19513186cdf0cdb42e4b9578cff66b1deaa3a80be160497692e7aea2a22b2cdc
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size 115400582
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:1a9300a898464f0950b7dd15b5de30f7c616f3fbd7bd959bacbd2ced97a228a2
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size 4472
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