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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fb1e40f38a4f65e5ba52072f358e8113a6903f02e8bbc7bacb5f4d000aaff39
- Size of remote file:
- 115 kB
- SHA256:
- f510f353536b28ff097d65631952fbcba458f68f047001b3b9ef0dc9b70f15c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.