Instructions to use AmineAllo/MT-ancient-spaceship-83 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmineAllo/MT-ancient-spaceship-83 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AmineAllo/MT-ancient-spaceship-83")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("AmineAllo/MT-ancient-spaceship-83") model = AutoModelForObjectDetection.from_pretrained("AmineAllo/MT-ancient-spaceship-83", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AmineAllo/MT-ancient-spaceship-83: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/AmineAllo/MT-ancient-spaceship-83/resolve/main/training_args.bin
- Command line
-
hf download hf://AmineAllo/MT-ancient-spaceship-83/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AmineAllo/MT-ancient-spaceship-83/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 86a8640ef14223cb0f4c7e047c92df5478e23b82671a6bdf434dd97bf31a1b45
- Size of remote file:
- 4.03 kB
- SHA256:
- 8e39c3e161fb0d6676789d933717fd8051c5aad2f19afeb9d5221f36e3703b85
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