Instructions to use BucketOfFish/huggingface_custom_model_tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BucketOfFish/huggingface_custom_model_tutorial with Transformers:
# Load model directly from transformers import AutoImageProcessor, ResnetModelForImageClassification processor = AutoImageProcessor.from_pretrained("BucketOfFish/huggingface_custom_model_tutorial") model = ResnetModelForImageClassification.from_pretrained("BucketOfFish/huggingface_custom_model_tutorial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from BucketOfFish/huggingface_custom_model_tutorial: direct link, hf CLI and curl.
- Browser
- Download file 103 MB
-
https://huggingface.co/BucketOfFish/huggingface_custom_model_tutorial/resolve/main/model.safetensors
- Command line
-
hf download hf://BucketOfFish/huggingface_custom_model_tutorial/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/BucketOfFish/huggingface_custom_model_tutorial/resolve/main/model.safetensors
103 MB
- Xet hash:
- a0e8f01d37949b6f9391313d20d135c75d3c23c9f7fa6f63dfaba6eaf4678e46
- Size of remote file:
- 103 MB
- SHA256:
- 78472643c5bb8b9614a3a08d815c1520408058f47e07b26a0e99918c1f7e3176
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.