Instructions to use TopKek/test2204 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TopKek/test2204 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="TopKek/test2204")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("TopKek/test2204") model = AutoModelForObjectDetection.from_pretrained("TopKek/test2204") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 200
Browse files- .gitignore +1 -0
- config.json +59 -0
- preprocessor_config.json +24 -0
- pytorch_model.bin +3 -0
- runs/Apr22_12-13-00_926a829f8126/1682165607.669653/events.out.tfevents.1682165607.926a829f8126.3059.1 +3 -0
- runs/Apr22_12-13-00_926a829f8126/events.out.tfevents.1682165607.926a829f8126.3059.0 +3 -0
- training_args.bin +3 -0
.gitignore
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checkpoint-*/
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config.json
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{
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"_commit_hash": "480370a8aeeed9fc8d78837b4e94e5f936fe73f2",
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"_name_or_path": "facebook/detr-resnet-50",
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"activation_dropout": 0.0,
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"activation_function": "relu",
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"architectures": [
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"DetrForObjectDetection"
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],
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"attention_dropout": 0.0,
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"auxiliary_loss": false,
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"backbone": "resnet50",
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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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"class_cost": 1,
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"classifier_dropout": 0.0,
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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": 0.1,
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"giou_cost": 2,
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"giou_loss_coefficient": 2,
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"id2label": {
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"0": "PLASTIC_BAG",
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"1": "PLASTIC_BOTTLE",
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"2": "OTHER_PLASTIC_WASTE",
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"3": "NOT_PLASTIC_WASTE"
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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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"NOT_PLASTIC_WASTE": 3,
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"OTHER_PLASTIC_WASTE": 2,
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"PLASTIC_BAG": 0,
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"PLASTIC_BOTTLE": 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": "detr",
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"num_channels": 3,
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"num_hidden_layers": 6,
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"num_queries": 100,
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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": "4.7.0.dev0",
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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": 1333,
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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 sha256:3a6b41a33525f9cf1202465e32c80c3fcfaa9d81efea78c0deb57f23e4fe7ea3
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size 166619173
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runs/Apr22_12-13-00_926a829f8126/1682165607.669653/events.out.tfevents.1682165607.926a829f8126.3059.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:952db0bda3a5e7075ba03fb515e4bb7970300bd94ce9d6a051af9bc47378e434
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size 5847
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runs/Apr22_12-13-00_926a829f8126/events.out.tfevents.1682165607.926a829f8126.3059.0
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version https://git-lfs.github.com/spec/v1
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size 5418
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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:d6dbf15dd72768a33fde5ab19e8024a25700015341fa3a4fb22b45ea123a2129
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size 3579
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