Instructions to use ivensamdh/fp16test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivensamdh/fp16test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ivensamdh/fp16test") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ivensamdh/fp16test") model = AutoModelForImageClassification.from_pretrained("ivensamdh/fp16test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17640be997249ef6c601b63dac4591e75ac55083d43bb6f44a45d1b64d5d6fb0
- Size of remote file:
- 172 MB
- SHA256:
- 7f50c7059b1fddf66ffdc1e1a96c2a4892740dce6481c082905456bff99ba5b2
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