Instructions to use hf-internal-testing/tiny-random-SegGptModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SegGptModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SegGptModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-SegGptModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SegGptModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-SegGptModel: direct link, hf CLI and curl.
- Browser
- Download file 115 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-SegGptModel/resolve/refs%2Fpr%2F39/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-SegGptModel@refs/pr/39/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-SegGptModel/resolve/refs%2Fpr%2F39/model.safetensors
115 kB
- Xet hash:
- 276c6840ef3fa319747121a94b0502f336070d4169fb78c08c414dd11464e156
- Size of remote file:
- 115 kB
- SHA256:
- 45e67ec6b2bd778097ed4d2ba965cdbbf2f427db1789c0f073049dfae760e561
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