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 pytorch_model.bin from AmineAllo/MT-ancient-spaceship-83: direct link, hf CLI and curl.
- Browser
- Download file 115 MB
-
https://huggingface.co/AmineAllo/MT-ancient-spaceship-83/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AmineAllo/MT-ancient-spaceship-83/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AmineAllo/MT-ancient-spaceship-83/resolve/main/pytorch_model.bin
115 MB
- Xet hash:
- 305c2043633a4b7ceb08bc46f733e74a4e6ff58b7462422ac7878d0f01dd989a
- Size of remote file:
- 115 MB
- SHA256:
- 42e4140dc5b44a5c875beb0b0c2cdc1453e76765d26471eff94a979e6fc84cb4
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