Instructions to use limehee/use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use limehee/use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="limehee/use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("limehee/use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("limehee/use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from limehee/use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/limehee/use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://limehee/use_data_finetuning@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/limehee/use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
167 MB
- Xet hash:
- 460275b488240096b32398e4123c4846fa030e0e3ca0b80cad0c7b8023025683
- Size of remote file:
- 167 MB
- SHA256:
- 609da6283d329b8a09e307df1b99852e3080bc6c0f4ffd427ff239afe74bf0b0
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