Instructions to use Alimuddin/amazon_fish_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alimuddin/amazon_fish_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Alimuddin/amazon_fish_classification") 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("Alimuddin/amazon_fish_classification") model = AutoModelForImageClassification.from_pretrained("Alimuddin/amazon_fish_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Alimuddin/amazon_fish_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Alimuddin/amazon_fish_classification/resolve/f0c4d3948c19dabbc3f1450eecb0cb42dd013f73/training_args.bin
- Command line
-
hf download hf://Alimuddin/amazon_fish_classification@f0c4d3948c19dabbc3f1450eecb0cb42dd013f73/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Alimuddin/amazon_fish_classification/resolve/f0c4d3948c19dabbc3f1450eecb0cb42dd013f73/training_args.bin
4.09 kB
- Xet hash:
- c14006abe081ec939248ec21ff833174d5787cb4251d1f03e3a1c2ad91d8a38f
- Size of remote file:
- 4.09 kB
- SHA256:
- 9bd65d9929e7df3343379a31a5a1308e4adeeccd13d3675fecfaeda48cfef7bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.