Instructions to use hf-internal-testing/tiny-random-PvtV2ForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtV2ForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-PvtV2ForImageClassification") 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("hf-internal-testing/tiny-random-PvtV2ForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-PvtV2ForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-PvtV2ForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 3.11 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-PvtV2ForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-PvtV2ForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-PvtV2ForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
3.11 MB
- Xet hash:
- b0301cdfe8c98a132143e11f8376ee6d6f1206741fd0a18dfbd51e432b6b652e
- Size of remote file:
- 3.11 MB
- SHA256:
- dbabfb45e5d259ad08e0d25480b3eb23dc65865e395c5ea3795d0dbdcaff5b4b
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