Instructions to use EverJun2/mlWeek7_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EverJun2/mlWeek7_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="EverJun2/mlWeek7_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("EverJun2/mlWeek7_2") model = AutoModelForObjectDetection.from_pretrained("EverJun2/mlWeek7_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from EverJun2/mlWeek7_2: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/EverJun2/mlWeek7_2/resolve/main/model.safetensors
- Command line
-
hf download hf://EverJun2/mlWeek7_2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/EverJun2/mlWeek7_2/resolve/main/model.safetensors
166 MB
- Xet hash:
- e8eca836689f6acf23be9e0a1dc610826421098675fc5f13875c8bbb75663714
- Size of remote file:
- 166 MB
- SHA256:
- 131af63bf0de0437b4a373c34e8c31b8b2b506998c61fdb453a7833f205da98e
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