Instructions to use arpanl/finetuned_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arpanl/finetuned_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="arpanl/finetuned_model") 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("arpanl/finetuned_model") model = AutoModelForImageClassification.from_pretrained("arpanl/finetuned_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from arpanl/finetuned_model: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/arpanl/finetuned_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://arpanl/finetuned_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/arpanl/finetuned_model/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 2e3625c8ac579401dedf47f35cd3ff1e4d69f5ef353c890c55a2af920c7275b7
- Size of remote file:
- 343 MB
- SHA256:
- a0960f1e93365b2283831adf2fe4bf2a1ea54d24d8123be323c62af70718434b
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