Instructions to use sameerrind009/visdrone-detr-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sameerrind009/visdrone-detr-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="sameerrind009/visdrone-detr-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("sameerrind009/visdrone-detr-finetuned") model = AutoModelForObjectDetection.from_pretrained("sameerrind009/visdrone-detr-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
visdrone-detr-finetuned
This model is a fine-tuned version of sameerrind009/visdrone-detr-finetuned on the None dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.45.2
- Pytorch 2.8.0+cu128
- Datasets 2.21.0
- Tokenizers 0.20.3
- Downloads last month
- 9
Model tree for sameerrind009/visdrone-detr-finetuned
Unable to build the model tree, the base model loops to the model itself. Learn more.