Mudassir41
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Parent(s):
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Upload RTDetrForObjectDetection
Browse files- README.md +199 -0
- config.json +100 -0
- model.safetensors +3 -0
README.md
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---
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library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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config.json
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{
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"_name_or_path": "PekingU/rtdetr_r50vd_coco_o365",
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"activation_dropout": 0.0,
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"activation_function": "silu",
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"anchor_image_size": null,
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"architectures": [
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"RTDetrForObjectDetection"
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],
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"attention_dropout": 0.0,
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"auxiliary_loss": true,
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"backbone": null,
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"backbone_config": {
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"model_type": "rt_detr_resnet",
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"out_features": [
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"stage2",
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"stage3",
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"stage4"
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],
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"out_indices": [
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2,
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4
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]
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},
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"backbone_kwargs": null,
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"batch_norm_eps": 1e-05,
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"box_noise_scale": 1.0,
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"d_model": 256,
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"decoder_activation_function": "relu",
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"decoder_attention_heads": 8,
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"decoder_ffn_dim": 1024,
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"decoder_in_channels": [
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256,
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256,
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256
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],
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"decoder_layers": 6,
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"decoder_n_points": 4,
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"disable_custom_kernels": true,
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"dropout": 0.0,
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"encode_proj_layers": [
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2
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],
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"encoder_activation_function": "gelu",
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"encoder_attention_heads": 8,
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"encoder_ffn_dim": 1024,
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"encoder_hidden_dim": 256,
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"encoder_in_channels": [
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512,
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1024,
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2048
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],
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"encoder_layers": 1,
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"eos_coefficient": 0.0001,
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"eval_size": null,
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"feat_strides": [
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8,
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16,
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32
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],
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"focal_loss_alpha": 0.75,
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"focal_loss_gamma": 2.0,
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"hidden_expansion": 1.0,
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"id2label": {
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"0": "can",
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"1": "heathly",
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"2": "sick"
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},
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"initializer_bias_prior_prob": null,
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"initializer_range": 0.01,
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"is_encoder_decoder": true,
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"label2id": {
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"can": 0,
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"heathly": 1,
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"sick": 2
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},
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"label_noise_ratio": 0.5,
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"layer_norm_eps": 1e-05,
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"learn_initial_query": false,
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"matcher_alpha": 0.25,
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"matcher_bbox_cost": 5.0,
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"matcher_class_cost": 2.0,
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"matcher_gamma": 2.0,
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"matcher_giou_cost": 2.0,
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"model_type": "rt_detr",
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"normalize_before": false,
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"num_denoising": 100,
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"num_feature_levels": 3,
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"num_queries": 300,
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"positional_encoding_temperature": 10000,
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"torch_dtype": "float32",
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"transformers_version": "4.44.0.dev0",
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"use_focal_loss": true,
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"use_pretrained_backbone": false,
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"use_timm_backbone": false,
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"weight_loss_bbox": 5.0,
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"weight_loss_giou": 2.0,
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"weight_loss_vfl": 1.0,
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"with_box_refine": true
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:162103d28c15207db6bd69cc6b85321e77bc3803e15dd9e3c5b069038843570a
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size 171542900
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