Instructions to use KasperRH/Raiyan_Kasper_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KasperRH/Raiyan_Kasper_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="KasperRH/Raiyan_Kasper_Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("KasperRH/Raiyan_Kasper_Model") model = AutoModelForObjectDetection.from_pretrained("KasperRH/Raiyan_Kasper_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KasperRH/Raiyan_Kasper_Model: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/KasperRH/Raiyan_Kasper_Model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KasperRH/Raiyan_Kasper_Model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KasperRH/Raiyan_Kasper_Model/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- c0b0a8807cb54d791cc34f6da6761a7b139583db2bef15ebc4fbc6623814ec1c
- Size of remote file:
- 167 MB
- SHA256:
- 20049bda49d55d38763f17edbbe28c3226aed0de102d08d4301804486f83b0a2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.