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:
- d853ae8881df733c08d6ba8c7742d64bcb397b41bdbccdcfa7a84c8a03663c3e
- Size of remote file:
- 115 kB
- SHA256:
- aa06ce5f5f8a918186858c2034b73542842049a6a780f9b191e4580493e34665
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.