Instructions to use roydcarlson/grain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roydcarlson/grain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="roydcarlson/grain") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("roydcarlson/grain") model = AutoModelForImageClassification.from_pretrained("roydcarlson/grain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from roydcarlson/grain: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/roydcarlson/grain/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://roydcarlson/grain/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/roydcarlson/grain/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- d1fc95657da62872f6e74af548c96957a0b62fb4fcf3f02ae2c157a0c6eb1792
- Size of remote file:
- 343 MB
- SHA256:
- e3590d92ce8aae0e4c3e94dcb99f3e658c4fb82adea761814f49f67d2342b114
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