Instructions to use AmineAllo/MT-chocolate-dust-79 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmineAllo/MT-chocolate-dust-79 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AmineAllo/MT-chocolate-dust-79")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("AmineAllo/MT-chocolate-dust-79") model = AutoModelForObjectDetection.from_pretrained("AmineAllo/MT-chocolate-dust-79", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AmineAllo/MT-chocolate-dust-79: direct link, hf CLI and curl.
- Browser
- Download file 115 MB
-
https://huggingface.co/AmineAllo/MT-chocolate-dust-79/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AmineAllo/MT-chocolate-dust-79/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AmineAllo/MT-chocolate-dust-79/resolve/main/pytorch_model.bin
115 MB
- Xet hash:
- eeb6744e31cbb5741a5e0c8a20e018023cf15c86046e5b33ea6f7ca24dc262ba
- Size of remote file:
- 115 MB
- SHA256:
- 68750accad369adef0d0114a46fe595a27a5f40cb22637cfc3803bbc59951c8c
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