Instructions to use binitt/buttons-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binitt/buttons-train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="binitt/buttons-train")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("binitt/buttons-train") model = AutoModelForObjectDetection.from_pretrained("binitt/buttons-train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from binitt/buttons-train: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/binitt/buttons-train/resolve/main/training_args.bin
- Command line
-
hf download hf://binitt/buttons-train/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/binitt/buttons-train/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- cbdd9a96340ebf7aaaa8aaf677550e1eef3307e6c1fe10b53ffec374145e390b
- Size of remote file:
- 4.6 kB
- SHA256:
- 5af6de552005a0f12b9e818100444e3fada70dc977d0a83a631103531c5d5777
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