Instructions to use sg485/optuna_table_transformer-orderstack-fine_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sg485/optuna_table_transformer-orderstack-fine_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="sg485/optuna_table_transformer-orderstack-fine_tuned")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("sg485/optuna_table_transformer-orderstack-fine_tuned") model = AutoModelForObjectDetection.from_pretrained("sg485/optuna_table_transformer-orderstack-fine_tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d948e4114f0dd1eca5ea3064e1c5baea705e139ed82610ef2ad3aa0b5b5a8816
- Size of remote file:
- 156 MB
- SHA256:
- 51c0a0fc81e400785503ddc7e8674fc5addaa6d07a06666675c24e45d392989b
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