Instructions to use SaysBlade/final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaysBlade/final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SaysBlade/final")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SaysBlade/final") model = AutoModelForObjectDetection.from_pretrained("SaysBlade/final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SaysBlade/final: direct link, hf CLI and curl.
- Browser
- Download file 26 MB
-
https://huggingface.co/SaysBlade/final/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://SaysBlade/final@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SaysBlade/final/resolve/refs%2Fpr%2F1/pytorch_model.bin
26 MB
- Xet hash:
- 6922b58807155931bf571b90d9e878b002a49e82114c87a094b882218c87bcfd
- Size of remote file:
- 26 MB
- SHA256:
- 0e3a7ad6d9164e938ac18995a888fe87cd76e7e3b8fdb9097cc1928912e21f38
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