Instructions to use hf-internal-testing/tiny-random-PhiModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PhiModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PhiModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PhiModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PhiModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e7d779a1b7d452c8b751f39cc2f6eda0103ae9be6bf76214007c04b2f86cd14
- Size of remote file:
- 188 kB
- SHA256:
- 574256a8d21c193a15ae51293f918f45bbbaeb7c9c2468ffbcc4aa2221407a65
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.