Instructions to use hf-tiny-model-private/tiny-random-OneFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-OneFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-OneFormerModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-OneFormerModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-OneFormerModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-OneFormerModel: direct link, hf CLI and curl.
- Browser
- Download file 47.8 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-OneFormerModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-OneFormerModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-OneFormerModel/resolve/refs%2Fpr%2F1/model.safetensors
47.8 MB
- Xet hash:
- 82b3036b4e17024754db246e90e9e41916af4f059c900ea0aa46982f083f2f8d
- Size of remote file:
- 47.8 MB
- SHA256:
- 5c8466e658d0ea1b6f7e5ff1b6ac2e971f3a191aa587548e63e5b2e6113405a3
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