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 training_args.bin from AmineAllo/MT-chocolate-dust-79: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/AmineAllo/MT-chocolate-dust-79/resolve/main/training_args.bin
- Command line
-
hf download hf://AmineAllo/MT-chocolate-dust-79/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AmineAllo/MT-chocolate-dust-79/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- e5ede215cb23c6331b8833190ff9b4802a4fef0f5036489cf47a2903c7985d00
- Size of remote file:
- 4.03 kB
- SHA256:
- bd7d61c61eb3aa22c0bcbc0545b4be2f1ba19b5e9778d25f773ced61297f52bc
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