Instructions to use MalyO2/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MalyO2/working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="MalyO2/working")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("MalyO2/working") model = AutoModelForObjectDetection.from_pretrained("MalyO2/working", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MalyO2/working: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/MalyO2/working/resolve/b26adbe23988dfea1ebd3d0a232a151608025402/training_args.bin
- Command line
-
hf download hf://MalyO2/working@b26adbe23988dfea1ebd3d0a232a151608025402/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MalyO2/working/resolve/b26adbe23988dfea1ebd3d0a232a151608025402/training_args.bin
5.24 kB
- Xet hash:
- 67b024a4d718fca4a4447555ab2cc305af9c5ba70807d6daa67c113bf3e4dda8
- Size of remote file:
- 5.24 kB
- SHA256:
- 5f7941a9f710b113017b974449691c8c6ff9f971a2dcf8cd8268a305306414d8
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