Instructions to use hf-internal-testing/tiny-random-GitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GitModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-GitModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-GitModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GitModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b1208f8d3dae76ee65dad054d5838f57ff7d17a81823e15efa0f53f21ad4b1e
- Size of remote file:
- 343 MB
- SHA256:
- a6f05c7f3caf8131add8ec78e2cce307234eb53e3da463e53cd53d6a8a66aa34
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.