Instructions to use changsu/testmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use changsu/testmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="changsu/testmodel") 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("changsu/testmodel") model = AutoModelForImageClassification.from_pretrained("changsu/testmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from changsu/testmodel: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/changsu/testmodel/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://changsu/testmodel@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/changsu/testmodel/resolve/refs%2Fpr%2F1/pytorch_model.bin
343 MB
- Xet hash:
- c79def71c4399d786385ca09b52419c2ad033d56709f0dcfe607bc2f447912c8
- Size of remote file:
- 343 MB
- SHA256:
- b24c08446d91b9e440b508d19d6d49b286e70b540bb5ec44e59c78cb4bebeb53
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