Instructions to use hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher: direct link, hf CLI and curl.
- Browser
- Download file 45.8 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher/resolve/refs%2Fpr%2F21/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher@refs/pr/21/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-EfficientFormerForImageClassificationWithTeacher/resolve/refs%2Fpr%2F21/model.safetensors
45.8 MB
- Xet hash:
- a1b9474f76d30dd37cc71b7b01b4d3db06f47443147dc30fb27a6529caa8c87a
- Size of remote file:
- 45.8 MB
- SHA256:
- 5cd95e48d0d4020fb6a82f158274cb32e2202b776b6306ff1ea7dd5f2d4fb76a
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