Instructions to use KrisLwin/convnext-tiny-finetuned-insectbites with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KrisLwin/convnext-tiny-finetuned-insectbites with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="KrisLwin/convnext-tiny-finetuned-insectbites") 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("KrisLwin/convnext-tiny-finetuned-insectbites") model = AutoModelForImageClassification.from_pretrained("KrisLwin/convnext-tiny-finetuned-insectbites", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KrisLwin/convnext-tiny-finetuned-insectbites: direct link, hf CLI and curl.
- Browser
- Download file 111 MB
-
https://huggingface.co/KrisLwin/convnext-tiny-finetuned-insectbites/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KrisLwin/convnext-tiny-finetuned-insectbites/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KrisLwin/convnext-tiny-finetuned-insectbites/resolve/main/pytorch_model.bin
111 MB
- Xet hash:
- 8aaa234c6bf1913daa055c4b42357238b2ac53f4273f68c5807527c994310ea0
- Size of remote file:
- 111 MB
- SHA256:
- 207ff8af60b5d9891104197297a3bf6ece3e5a25fffb93d37ea94e6c99e604b6
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