Instructions to use hf-internal-testing/tiny-random-big_bird with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-big_bird with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-big_bird")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-big_bird") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-big_bird") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acf0adb36c3a7111d1a66162f298c0955680d93eacc385a052e1ae79b60711cf
- Size of remote file:
- 253 kB
- SHA256:
- 8dfd1eae4522281b1b839eab877a791befec7a1663a41c814c77d9c89c748f2d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.